Knockdown of the atypical protein kinase genes GhABC1K2-A05 and GhABC1K12-A07 make cotton more sensitive to salt and PEG stress

Activity of bc1 complex kinase(ABC1K)is an atypical protein kinase(aPK)that plays a crucial role in plant mitochondrial and plastid stress responses,but little is known about the responses of ABC1Ks to stress in cotton(Gossypium spp.).Here,we identified 40 ABC1Ks in upland cotton(Gossypium hirsutum L.)and found that the Gh ABC1Ks were unevenly distributed across 17 chromosomes.The GhABC1K family members included 35 paralogous gene pairs and were expanded by segmental duplication.The GhABC1K promoter sequences contained diverse cis-acting regulatory elements relevant to hormone or stress responses.The qRT-PCR results revealed that most Gh ABC1Ks were upregulated by exposure to different stresses.Gh ABC1K2-A05 and Gh ABC1K12-A07 expression levels were upregulated by at least three stress treatments.These genes were further functionally characterized by virus-induced gene silencing(VIGS).Compared with the controls,the Gh ABC1K2-A05-and Gh ABC1K12-A07-silenced cotton lines exhibited higher malondialdehyde(MDA)contents,lower catalase(CAT),peroxidase(POD)and superoxide dismutase(SOD)activities and reduced chlorophyll and soluble sugar contents under NaCl and PEG stress.In addition,the expression levels of six stress marker genes(Gh DREB2A,Gh SOS1,Gh CIPK6,Gh SOS2,Gh WRKY33,and Gh RD29A)were significantly downregulated after stress in the Gh ABC1K2-A05-and Gh ABC1K12-A07-silenced lines.The results indicate that knockdown of Gh ABC1K2-A05 and Gh ABC1K12-A07 make cotton more sensitive to salt and PEG stress.These findings can provide valuable information for intensive studies of Gh ABC1Ks in the responses and resistance of cotton to abiotic stresses.

Design and implementation of the monochromator shielding for the cold neutron spectrometers XINGZHI and BOYA

An innovative monochromator shielding is designed and implemented for the cold neutron spectrometers XINGZHI and BOYA operated by Renmin University of China at China Advanced Research Reactor.Via Monte Carlo simulations and careful mechanical designs,a shielding configuration has been successfully developed to satisfy safety requirements of below 3μSv/h dose rate at its exterior,meanwhile fulfilling space,floor load and nonmagnetic requirements.Composite materials are utilized to form the sandwich-type shielding walls:the inner layer of boron carbide rubber,the middle layer of steel-encased lead and the outer layer of borated polyethylene.Special-shaped liftable shielding blocks are incorporated to facilitate a continuous adjustment of the neutron energy while preventing radiation leakage.Our work has demonstrated that by utilizing composite shielding materials,along with the sandwich structure and liftable shielding blocks,a compact and lightweight shielding solution can be achieved.This enables the realization of advanced neutron scattering instruments that provide expanded space of measurement,larger energy and momentum coverage,and higher flux on the sample.This shielding represents the first of its kind in neutron scattering instruments in China.Following its successful operation,it has been subsequently employed by other neutron instruments across the country.

A Neural-network-based Alternative Scheme to Include Nonhydrostatic Processes in an Atmospheric Dynamical Core

Here,a nonhydrostatic alternative scheme(NAS)is proposed for the grey zone where the nonhydrostatic impact on the atmosphere is evident but not large enough to justify the necessity to include an implicit nonhydrostatic solver in an atmospheric dynamical core.The NAS is designed to replace this solver,which can be incorporated into any hydrostatic models so that existing well-developed hydrostatic models can effectively serve for a longer time.Recent advances in machine learning(ML)provide a potential tool for capturing the main complicated nonlinear-nonhydrostatic relationship.In this study,an ML approach called a neural network(NN)was adopted to select leading input features and develop the NAS.The NNs were trained and evaluated with 12-day simulation results of dry baroclinic-wave tests by the Weather Research and Forecasting(WRF)model.The forward time difference of the nonhydrostatic tendency was used as the target variable,and the five selected features were the nonhydrostatic tendency at the last time step,and four hydrostatic variables at the current step including geopotential height,pressure in two different forms,and potential temperature,respectively.Finally,a practical NAS was developed with these features and trained layer by layer at a 20-km horizontal resolution,which can accurately reproduce the temporal variation and vertical distribution of the nonhydrostatic tendency.Corrected by the NN-based NAS,the improved hydrostatic solver at different horizontal resolutions can run stably for at least one month and effectively reduce most of the nonhydrostatic errors in terms of system bias,anomaly root-mean-square error,and the error of the wave spatial pattern,which proves the feasibility and superiority of this scheme.

Assimilation of the FY-4A AGRI Clear-Sky Radiance Data in a Regional Numerical Model and Its Impact on the Forecast of the“21·7”Henan Extremely Persistent Heavy Rainfall

Assimilation of the Advanced Geostationary Radiance Imager(AGRI)clear-sky radiance in a regional model is performed.The forecasting effectiveness of the assimilation of two water vapor(WV)channels with conventional observations for the“21·7”Henan extremely heavy rainfall is analyzed and compared with a baseline test that assimilates only conventional observations in this study.The results show that the 24-h cumulative precipitation forecast by the assimilation experiment with the addition of the AGRI exceeds 500 mm,compared to a maximum value of 532.6 mm measured by the national meteorological stations,and that the location of the maximum precipitation is consistent with the observations.The results for the short periods of intense precipitation processes are that the simulation of the location and intensity of the 3-h cumulative precipitation is also relatively accurate.The analysis increment shows that the main difference between the two sets of assimilation experiments is over the ocean due to the additional ocean observations provided by FY-4A,which compensates for the lack of ocean observations.The assimilation of satellite data adjusts the vertical and horizontal wind fields over the ocean by adjusting the atmospheric temperature and humidity,which ultimately results in a narrower and stronger WV transport path to the center of heavy precipitation in Zhengzhou in the lower troposphere.Conversely,the WV convergence and upward motion in the control experiment are more dispersed;therefore,the precipitation centers are also correspondingly more dispersed.

英国国家科研与创新署学科交叉研究资助机制及启示

自2018年成立以来,英国国家科研与创新署(UKRI)整合了以学科为基础划分的英国七大研究理事会和英国创新署、英格兰研究署,显著增强了英国科研与创新体系的战略协同。通过九个下属机构的横向联合,UKRI在一批重点领域资助了多个学科交叉项目。此外,UKRI还通过战略优先基金支持面向国家战略需求的学科交叉研究,通过全球挑战研究基金促进以学科交叉手段解决发展中国家面临的共性挑战。在学科交叉项目的立项和管理过程中,UKRI重视与政府、大学、非政府组织以及产业界的合作,并采取一系列手段改善学科交叉项目的评审效果。UKRI的举措对我国科研创新资助机构推动学科交叉发展具有多方面的借鉴意义,如优化资助格局、完善跨学科跨部门协作机制、加强与政府和企业的合作、以及改进评审机制等。

Green catalytic oxidation of benzyl alcohol over Pt/ZnO in base‐free aqueous medium at room temperature

The selective oxidation of alcohol using molecular oxygen as an oxidant and water as a green sol‐vent is of great interest in green chemistry. In this work, we present a systematic study of a Pt/ZnO catalyst for the selective oxidation of benzyl alcohol at room temperature under base‐free aqueous conditions. Experimental observations and density functional theory calculations suggest that ZnO as a support can facilitate the adsorption of benzyl alcohol, which subsequently reacts with the activated oxygen species on the Pt catalyst, producing benzaldehyde. The resulting solid achieves a high conversion（94.1 ± 5.1% in 10 h） of benzyl alcohol and nearly 100% selectivity to benzalde‐hyde with ambient air as the oxidant. In addition, by introducing a small amount of Bi（1.78 wt%） into Pt/ZnO, we can further enhance the activity by 350%.

Surface coupling of methyl radicals for efficient low‐temperature oxidative coupling of methane

Selective coupling of methyl radicals to produce C_(2) species(C2H4 and C2H6)is a key challenge for oxidative coupling of methane(OCM).In traditional OCM reaction systems,homogeneous transformation of methyl radicals in O_(2)‐containing gases are uncontrollable,resulting in limited C_(2) selectivity and yield.Herein,we demonstrate that methyl radicals generated by La_(2)O_(3)at low reaction temperature can selectively couple on the surface of 5 wt%Na2WO4/SiO_(2).The controllable surface coupling against overoxidation barely changes the activity of La_(2)O_(3)but boosts the C_(2)selectivity by three times and achieves a C_(2)yield as high as 10.9%at bed temperature of only 570℃.Structure‐property studies suggest that Na_(2)WO_(4) nanoclusters are the active sites for methyl radical coupling.The strong CH_(3)·affinity of these sites can even endow some methane combustion catalysts with OCM activity.The findings of the surface coupling of methyl radicals open a new direction to develop OCM catalyst.The bifunctional OCM catalyst system,which composes of a methane activation center and a CH_(3)·coupling center,may deliver promising OCM performance at reaction temperatures below the ignition temperature of C2H6 and C2H4(~600℃)and is therefore more controllable,safer,and certainly more attractive as an actual process.

Application and Characteristic Analysis of the Moist Singular Vector in GRAPES-GEPS

The singular vector(SV)initial perturbation method can capture the fastest-growing initial perturbation in a tangent linear model(TLM).Based on the global tangent linear and adjoint model of GRAPES-GEPS(Global/Regional Assimilation and Prediction System-Global Ensemble Prediction System),some experiments were carried out to analyze the structure of the moist SVs from the perspectives of the energy norm,energy spectrum,and vertical structure.The conclusions are as follows:The evolution of the SVs is synchronous with that of the atmospheric circulation,which is flowdependent.The moist and dry SVs are located in unstable regions at mid-to-high latitudes,but the moist SVs are wider,can contain more small-and medium-scale information,and have more energy than the dry SVs.From the energy spectrum analysis,the energy growth caused by the moist SVs is reflected in the relatively small-scale weather system.In addition,moist SVs can generate perturbations associated with large-scale condensation and precipitation,which is not true for dry SVs.For the ensemble forecasts,the average anomaly correlation coefficient of large-scale circulation is better for the forecast based on moist SVs in the Northern Hemisphere,and the low-level variables forecasted by the moist SVs are also improved,especially in the first 72 h.In addition,the moist SVs respond better to short-term precipitation according to statistical precipitation scores based on 10 cases.The inclusion of the large-scale condensation process in the calculation of SVs can improve the short-term weather prediction effectively.

A new method for multi-point pollution source identification

Rapid and accurate identification of the characteristics(source location,number,and intensity)of pollution sources is essential for emergency assessment of contamination events.Compared with single-point source iden-tification,the reconstruction of multiple sources is more challenging.In this study,a two-step inversion method is proposed for multi-point pollution source reconstruction from limited measurements with the number of sources unknown.The applicability of the proposed method is validated with a set of synthetic experiments correspond-ing to one-,two-,and three-point pollution sources.The results show that the number and locations of pollution sources are retrieved exactly the same as prescribed,and the source intensities are estimated with negligible errors.The algorithm exhibits good performance in single-and multi-point pollution source identification,and its accuracy and efficiency of identification do not deteriorate with the increase in the number of sources.Some limitations of the algorithm,together with its capabilities,are also discussed in this paper.

Site-specific deposition creates electron-rich Pd atoms for unprecedented C-H activation in aerobic alcohol oxidation

Here,we demonstrate a photochemical strategy to site-specifically deposit Pd atoms on Au nanoparticles.The high-sensitivity low-energy ion scattering spectra combined with the X-ray photoelectron spectra reveal that the surface electronic structure of Pd can be continuously regulated by tailoring the Pd-to-Au molar ratio and the location of Pd atoms in Au Pd nanoparticles.It is revealed that electron-rich Pd atoms are considerably more active than the net Pd atoms in aerobic alcohol oxidation.Remarkably,the catalyst with the most electron-rich Pd sites(binding energy downshift:1.0 e V)exhibits an extremely high turnover frequency(~500000 h-1 vs 12000 h-1 for that with net Pd atoms)for solvent-free selective oxidation of benzyl alcohol,which is,to the best of our knowledge,the highest value ever reported.Kinetic studies reveal that electron-rich Pd atoms can accelerate the oxidation of benzyl alcohol by facilitating C-H cleavage,as indicated by the significant reduction in the activation energy as compared to net Pd atoms.

Tuning catalytic selectivity of propane oxidative dehydrogenation via surface polymeric phosphate modification on nickel oxide nanoparticles

Thermal stability has long been recognized as a major limitation for the application of ligand modification in high-temperature reactions. Herein, we demonstrate polymeric phosphate as an efficient and stable ligand to tune the selectivity of propane oxidative dehydrogenation. Beneficial from the weakened affinity of propene, NiO modified with polymeric phosphate shows a selectivity 2–3 times higher than NiO towards the production of propene. The success of this regulation verifies the feasibility of ligand modification in high-temperature gas-phase reactions and shines a light on its applications in other important industrial reactions.

Variational Quality Control of Non-Gaussian Innovations in the GRAPES m3DVAR System: Mass Field Evaluation of Assimilation Experiments

The existence of outliers can seriously influence the analysis of variational data assimilation.Quality control allows us to effectively eliminate or absorb these outliers to produce better analysis fields.In particular,variational quality control(VarQC) can process gray zone outliers and is thus broadly used in variational data assimilation systems.In this study,governing equations are derived for two VarQC algorithms that utilize different contaminated Gaussian distributions(CGDs): Gaussian plus flat distribution and Huber norm distribution.As such,these VarQC algorithms can handle outliers that have non-Gaussian innovations.Then,these VarQC algorithms are implemented in the Global/Regional Assimilation and PrEdiction System(GRAPES) model-level three-dimensional variational data assimilation(m3 DVAR) system.Tests using artificial observations indicate that the VarQC method using the Huber distribution has stronger robustness for including outliers to improve posterior analysis than the VarQC method using the Gaussian plus flat distribution.Furthermore,real observation experiments show that the distribution of observation analysis weights conform well with theory,indicating that the application of VarQC is effective in the GRAPES m3 DVAR system.Subsequent case study and longperiod data assimilation experiments show that the spatial distribution and amplitude of the observation analysis weights are related to the analysis increments of the mass field(geopotential height and temperature).Compared to the control experiment,VarQC experiments have noticeably better posterior mass fields.Finally,the VarQC method using the Huber distribution is superior to the VarQC method using the Gaussian plus flat distribution,especially at the middle and lower levels.

The facile method developed for preparing polyvinylidene fluoride plasma separation membrane via macromolecular interaction

The design of membrane pore is critical for membrane preparation. Polyvinylidene fluoride(PVDF) membrane exhibits outstanding properties in the water-treatment field. However, it is a huge challenge to prepare PVDF macro-pore plasma separation membrane by non-solvent induced phase separation(NIPS). Herein, a facile strategy is proposed to prepare PVDF macro-pore plasma separation membrane via macromolecular interaction. ATR-FTIR and ^(1)H NMR showed that the intermolecular interaction existed between polyethylene oxide(PEO) and polyvinylpyrrolidone(PVP). It could significantly affect the PVDF macro-pore membrane structure. The maximum pore of the PVDF membrane could be effectively adjusted from small-pore/medium-pore to macro-pore by changing the molecular weight of PEO. The PVDF macro-pore membrane was obtained successfully when PEO-200 k existed with PVP. It exhibited higher plasma separation properties than the currently used plasma separation membrane.Moreover, it had excellent hemocompatibility due to the similar plasma effect, hemolysis, prothrombin time, blood effect and complement C_(3a) effect with the current utilized plasma separation membrane,implying its great potential application. The proposed facile strategy in this work provides a new method to prepare PVDF macro-pore plasma separation membrane by NIPS.

Model Uncertainty Representation for a Convection-Allowing Ensemble Prediction System Based on CNOP-P

Formulating model uncertainties for a convection-allowing ensemble prediction system(CAEPS)is a much more challenging problem compared to well-utilized approaches in synoptic weather forecasting.A new approach is proposed and tested through assuming that the model uncertainty should reasonably describe the fast nonlinear error growth of the convection-allowing model,due to the fast developing character and strong nonlinearity of convective events.The Conditional Nonlinear Optimal Perturbation related to Parameters(CNOP-P)is applied in this study.Also,an ensemble approach is adopted to solve the CNOP-P problem.By using five locally developed strong convective events that occurred in pre-rainy season of South China,the most sensitive parameters were detected based on CNOP-P,which resulted in the maximum variations in precipitation.A formulation of model uncertainty is designed by adding stochastic perturbations into these sensitive parameters.Through comparison ensemble experiments by using all the 13 heavy rainfall cases that occurred in the flood season of South China in 2017,the advantages of the CNOP-P-based method are examined and verified by comparing with the well-utilized stochastically perturbed physics tendencies(SPPT)scheme.The results indicate that the CNOP-P-based method has potential in improving the under-dispersive problem of the current CAEPS.

Property and performance amelioration of pelagic clay from the East Pacific

To make use of the pelagic clay as polymer filling,the properties of clay sediments from the ocean investigation zone of China in the East Pacific were studied by the SSA,XRF,ICP/MAS,FTIR,XRD,SEM,DTA/TG and granularity distributing etc.,and experiments were settled to improve the whiteness and activation of the clay based on these data.Compared with land clay,pelagic clay holds many particular features,such as fine particles and incompact accumulation,worse crystallization and more defects,high activity,complex mineral and chemical components,and low whiteness etc.Processing the purified pelagic clay with acids and zinc,then baked it at different temperatures,the whiteness of clay can be increased from 23.8% to 73.1%,and the optimized conditions is:consistency of vitriol 25%,ratio of clay to water 4∶1,reaction time 4h,reaction temperature 90℃,dosage of zinc 2.0 g/L,and baking temperature 700℃.And the SSA of whited clay is increased too.Using the dry milling method to modify the pelagic clay with organic reagents,the optimized technique is KH550,concentration 1.5%,reaction time 20 min.XRD,FTIR and SEM testing indicate that the mechanism of organic activation was mainly surface absorbing and chemical combination secondly.

Daicong solution effects on brain ultrastructure in a rat model of Alzheimer's disease

BACKGROUND： Infusion of kainic acid into the basal nuclei induces neuronal excitotoxicity, degeneration and necrosis, resulting in disturbed learning and memory functions. OBJECTIVE： To explore the effects of different doses of traditional Chinese medicine Daicong solution on brain ultrastructure in a rat model of Alzheimer＇s disease. DESIGN, TIME AND SETTING： The randomized, controlled, cellular morphology experiment was performed at the Shandong Provincial Key Laboratory of Molecular Immunology of Weifang Medical University, China from October 2006 to March 2007. MATERIALS： Fifty healthy, Sprague Dawley rats, aged 22-months, were used to establish rat models of Alzheimer＇s disease. The Morris water maze was prepared at the Pharmacometrics Key Laboratory of Weifang Medical University in Shandong Province of China. Traditional Chinese medicine Daicong solution （crude drug 1 g/mL）, composed of radix ginseng, rehmannia dried rhizome, anemarrhenae and radix astragali, was produced by the Department of Pharmacy of Hospital Affiliated to Weifang Medical University. Kainic acid was provided by Professor Xiuyan Li from Weifang Medical University. METHODS： A total of 40 model rats were equally and randomly divided into four groups： dementia model, low-dose Daicong solution （5 g/kg/d）, moderate-dose Daicong solution （10 g/kg/d）, and high-dose Daicong solution （20 g/kg/d）. An additional 10 healthy rats served as the normal control group. Rats in the dementia model and normal control groups received saline （10 mL/kg/d）. MAIN OUTCOME MEASURES： Neural cell ultrastructure was observed utilizing electron microscopy after 1 month of respective treatments. RESULTS： Compared with the normal control group, electron density and the number of ribosomes were significantly reduced in neuronal cytoplasm, and many lipofuscin grains and vacuole-like changes were observed in mitochondria in the dementia model group. In addition, nuclear chromatin presented with different sizes of plaque-shaped degenerative pathological changes. In the Alzheimer＇s disease rat model, neurons and neuroepithelial cells recovered to normal conditions following treatment with moderate- and high-dose Daicong solution. In the low-dose Daicong group, the condition was slightly improved, but the cytopathic effects were still significant. CONCLUSION： Daicong solution significantly improved neuronal and neuroepithelial pathological ultrastructure in a rat model of Alzheimer＇s disease.

Inversion method for multi-point source pollution identification:Sensitivity analysis and application to European Tracer Experiment data

Fast and accurate identification of unknown pollution sources plays a crucial role in the emergency response and source control of air pollution.In this work,the applicability of a previously proposed two-step inversion method is investigated with sensitivity experiments and real data from the first release of the European Tracer Experiment(ETEX-1).The two-step inversion method is based on the principle of least squares and carries out additional model correction through the residual iterative process.To evaluate its performance,its retrieval results are compared with those of two other existing algorithms.It is shown that for those cases with richer measurements,all three methods are less sensitive to errors,while for cases where measurements are sparse,their retrieval accuracy will rapidly decrease as errors increase.From the results of sensitivity experiments,the new method provides higher estimation accuracy and a more stable performance than the other two methods.The new method presents the smallest maximum location error of 18.20 km when the amplitude of the measurement error increases to 100%,and 22.67 km when errors in the wind fields increase to 200%.Moreover,when applied to ETEX-1 data,the new method also exhibits good performance,with a location error of 4.71 km,which is the best estimation with respect to source location.

A single-crystal neutron diffraction study on magnetic structure of CsCo_2Se_2

The magnetic structure of CsCo_2 Se_2 was investigated using single-crystal neutron diffraction technique. An antiferromagnetic transition with the propagation vector（0,0,1） was observed at TN= 78 K. The Co magnetic moment 0.772（6） μB at 10 K pointing in the basal plane couples ferromagnetically in the plane, which stacks antiferromagnetically along the c direction. Tuning and suppressing the interplane antiferromagnetic interaction may be crucial to induce a superconducting state in the material.

Comprehensive Benefit Analysis of Direct Expansion Ground Source Heat Pump System

Direct Expansion Ground Source Heat Pump (DXGSHP) system directly extracts heat or cold energy from ground by consuming electricity to provide for space conditioning. Compared with the currently widely-used secondary loop Ground Couple Heat Pump (GCHP) system, it has higher energy efficiency, lower operating costs, and less environmental impact. A case study is carried out in this paper. The subject is a residential building located in Beijing, China. It is assumed that the building adopts the DXGSHP system and the GCHP system respectively. Annual loads and energy consumption are simulated and computed. Then the initial cost, operating cost and CO2 emission are calculated. The economic benefit is analyzed with the Payback Time method and the Dynamic Annual Cost Value method. The environmental benefit is discussed mainly by comparing the CO2 emission savings. The results show that the DXGSHP system has higher initial costs, but lower operating costs, and less greenhouse gas emissions. The DXGSHP system has better comprehensive benefits than the GCHP system.

Synchronously Detecting Allergenic Ingredients of Peanut and Sesame in Food by Real-time Fluorescent PCR

Peanut,sesame and other raw materials of food are allergens for special populations.In this study,specific primers and TaqMan probes labeled by different fluorescences were designed targeting Ara h 2 gene of peanut and Ses i 1 gene of sesame.After the optimization of reaction conditions,a real-time fluorescent PCR method was established for simultaneous detection of allergenic ingredients of peanut and sesame in food.Genomic DNA samples of peanut,sesame,rice,wheat,barley,soybean,celery,maize,potato,tomato,walnut,groundnut in shell,cashew nut,sunflower seed,almond,apple,pear and strawberry,pork,beef,mutton and fish were used as templates for PCR amplification with deionized water as negative control template.Results indicated that the established real-time fluorescent PCR method could specifically identify allergenic ingredients of peanut and sesame simultaneously.Sensitivity test showed that the minimum detection limit of this method was 0.01%.Therefore,the established real-time fluorescent PCR method is a specific,sensitive and effective assay for simultaneously detecting allergenic ingredients of peanut and sesame in food.