Enabling heterogeneous catalysis to achieve carbon neutrality: Directional catalytic conversion of CO_(2) into carboxylic acids

The increase in anthropogenic carbon dioxide(CO_(2))emissions has exacerbated the deterioration of the global environment,which should be controlled to achieve carbon neutrality.Central to the core goal of achieving carbon neutrality is the utilization of CO_(2) under economic and sustainable conditions.Recently,the strong need for carbon neutrality has led to a proliferation of studies on the direct conversion of CO_(2) into carboxylic acids,which can effectively alleviate CO_(2) emissions and create high-value chemicals.The purpose of this review is to present the application prospects of carboxylic acids and the basic principles of CO_(2) conversion into carboxylic acids through photo-,electric-,and thermal catalysis.Special attention is focused on the regulation strategy of the activity of abundant catalysts at the molecular level,inspiring the preparation of high-performance catalysts.In addition,theoretical calculations,advanced technologies,and numerous typical examples are introduced to elaborate on the corresponding process and influencing factors of catalytic activity.Finally,challenges and prospects are provided for the future development of this field.It is hoped that this review will contribute to a deeper understanding of the conversion of CO_(2) into carboxylic acids and inspire more innovative breakthroughs.

Optical storage of circular airy beam in atomic vapor

The realization of quantum storage of spatial light field is of great significance to the construction of high-dimensional quantum repeater.In this paper,we experimentally realize the storage and retrieval of circular Airy beams(CABs)by using theΛ-type three-level energy system based on the electromagnetically induced transparency in a hot rubidium atomic vapor cell.The weak probe beam field is modulated with phase distribution of CABs by a spatial light modulator.We store the probe circular Airy beam(CAB)into the rubidium atomic vapor cell and retrieve it after the demanded delay.We quantitatively analyze the storage results and give corresponding theoretical explanations.Moreover,we investigate the autofocusing and self-healing effect of the retrieved CAB,which indicates that the properties and beam shape of CAB maintain well after storage.Our work will have potential applications in the storage of high-dimensional quantum information,and is also useful for improving the channel capacities of quantum internet.

The Error Compensation of Inclinometer Based on Polynomial Fitting

In order to reduce the influence of nonlinear characteristic and temperature on the measuring accuracy of inclinometer, the application of polynomial fitting principle to compensate the measuring error of inclinometer is studied. According to the analysis of the experimental data of inclinometer, a polynomial model of the nonlinear error and the measured value is constructed, and then the relation between the coefficient of the polynomial model and the temperature is obtained by fitting, and finally the function of the measurement error of inclinometer on the measured inclination and temperature is obtained. The results show that this method is feasible and effective, which can not only reduce the influence of temperature, but also correct its nonlinear error.

Simulation Analysis of Transponder Power Based on Target Flight Trajectory

The directional angle of the exterior trajectory measurement equipment in the transponder antenna coordinate system is an important basis for interpreting the transponder antenna gain, analyzing the uplink and downlink power of the transponder, and evaluating the measurement and tracking ability of the equipment. The mathematical model established in this paper deduces the direction angle of the exterior trajectory measurement equipment in the transponder antenna coordinate system according to the track information of the flight target, and then obtains the transponder power received by the exterior trajectory measurement equipment combined with the installation position of the transponder, the antenna pattern and the secondary radar formula. It can effectively evaluate the tracking ability of the equipment in measuring segment and adjust the working state of the equipment according to the actual situation. At the same time, it provides a theoretical basis for the ground measurement equipment to receive the transponder power is too low, resulting in the measurement data accuracy is not up to standard, or even lost.

Angle estimation in bistatic MIMO radar using improved reduced dimension Capon algorithm

This paper discusses the problem of direction of departure （DOD） and direction of arrival （DOA） estimation for a bistatic multiple input multiple output （MIMO） radar, and proposes an improved reduced-dimension Capon algorithm therein. Compared with the reduced-dimension Capon algorithm which requires pair matching between the two-dimensional angle estimation, the pro- posed algorithm can obtain automatically paired DOD and DOA estimation without debasing the performance of angle estimation in bistatic MIMO radar. Furthermore, the proposed algorithm has a lower complexity than the reduced-dimension Capon algorithm, and it is suitable for non-uniform linear arrays. The complexity of the proposed algorithm is analyzed and the Cramer-Rao bound （CRB） is also derived. Simulation results verify the usefulness of the proposed algorithm.

Genetic relationship and pedigree of Chinese watermelon varieties based on diversity of perfect SNPs

Watermelon(Citrullus lanatus)is one of the world’s most important fruit crops,and China produces the most watermelons in the world.Recently,a watermelon variome consisting of 414 key resequenced accessions was reported.However,the genetic relationships and pedigree of Chinese watermelon varieties in the seed market remain unclear.In this study,241 evenly distributed perfect single nucleotide polymorphisms(SNPs)derived from the watermelon variome were selected for variety identification.The diversity of 247 Chinese watermelon varieties was identified based on their SNP genotypes.The 247 watermelon varieties were clustered into five subpopulations:the East Asian ecotype,intermediate ecotype,small fruit with red flesh ecotype,small fruit with yellow flesh ecotype,and American ecotype.We further established the pedigree of four subpopulations,of which JingXinNo.1,ZaoChunHongYu,HuangXiaoYu and XiaoLan,and Sugarlee were the main doner of the East Asian ecotype,small fruit with red flesh ecotype,small fruit with yellow flesh ecotype,and American ecotype,respectively.Thirty-two core SNPs were selected and applied in watermelon variety identification.They were also validated by the Kompetitive allele-specific PCR(KASPar)platform.The present study furthered our understanding of the genetic relationships and pedigree of watermelon varieties in China,and will help to manage the plant variety protection in watermelon.

Fast multi-parameter estimation and localization for MIMO radar

This paper addresses the problem of four-dimensional angle and Doppler frequency estimation for bistatic multiple-input multiple-output （MIMO） radar with arbitrary arrays in spatial co- lored noise. A novel method for joint estimation of Doppler fre- quency, two-dimensional （2D） direction of departure and 2D direc- tion of arrival based on the propagator method （PM） for arbitrary arrays is discussed. A special matrix is constructed to eliminate the influence of spatial colored noise. The four-dimensional （4D） angle and Doppler frequency are extracted from the matrix and the three- dimensional （3D） coordinates of the targets are then calculated on the basis of these angles. The proposed algorithm provides a lower computational complexity and has a parameter estimation very close to that of the ESPRIT algorithm and the DOA-matrix al- gorithm in the high signal to noise ratio and the Cramer-Rao bound （CRB） is given. Furthermore, multi-dimensional parameters can be automatically paired by this algorithm to avoid performance degra- dation resulting from wrong pairing. Simulation results demonstrate the effectiveness of the proposed method.

Adaptive Cascaded High-Resolution Source Localization Based on Collaboration of Multi-UAVs

Effective information fusion is very important in hybrid source localization. In this paper, the performance analysis of conventional joint direction of arrival(DOA) and time difference of arrival(TDOA) system is derived and it is shown that this hybrid system may inferior to the single system when the ratio of angular measurements error to distance measurements error exceeds a threshold. To avoid this problem, an effective DOA/TDOA adaptive cascaded(DTAC) technique is presented. The rotation feature of UAVs and spatial filtering technique are applied to gain the signal-to-noise ratio(SNR), which leads to more accurate estimation of time delay by using DOAs. Nevertheless, the time delay estimation precision is still limited by the sampling frequency, which is constrained by the finite load of UAV. To break through the limitation, an enhanced self-delay-compensation(SDC) method is proposed, which aims at detecting the overlooked time delay within the sampling interval by adding a tiny time delay. Finally, the position of the source is estimated by the Chan algorithm. Compared to DOA-only algorithm, TDOA-only algorithm and joint DOA/TDOA(JDT) algorithm, the proposed method shows better localization accuracy regardless of different SNRs and sampling frequencies. Numerical simulations are presented to validate the effectiveness and robustness of the proposed algorithm.

Comparison of DUS testing and SNP fingerprinting for variety identification in cucumber

Variety identification plays an important role in protecting the intellectual property of varieties,ensuring seed quality,and encouraging breeding innovation.Currently,morphological evaluation in the field,such as distinctness,uniformity,and stability(DUS)testing,and DNA fingerprinting in the laboratory using molecular markers are two dominant methods used for variety identification.Few studies have compared the results of these approaches,and the relationship between the two methods is obscure.In this study,134 dominant cucumber varieties were evaluated using 50 DUS testing traits and genotyped by 40 single nucleotide polymorphisms(SNPs).The 40 SNPs were developed in our previous study and arewell suited for variety identification.In the DUS testing,significant positive or negative correlations among 50 DUS traits were observed,and 20 core traits,including 15 fruit traits,were further selected to increase field inspection efficiency.This suggested that fruit shape plays an important role in variety identification.The ratio of fruit length/diameter was themost important trait,explaining 9.2%of the phenotypic variation.In the DNA fingerprinting test,the 40 SNPs were highly polymorphic and could distinguish all of the 134 cucumber varieties,and 14 core SNPs were selected to improve the identification rate.Interestingly,the population structure analysis of 134 cucumber varieties by phenotypic data in the DUS test was in accordance with the genotypic data from the DNA fingerprinting,indicating that all varieties could be divided into the same four subgroups:European type,North China type,South China type,and hybrids of the North China and South China types.Moreover,linear correlativity of distinguishment for each pair of varieties was observed between the DUS test and the DNA fingerprinting.These results indicated that these two methods have good application in future research,especially for the scaled-up analysis of hundreds of varieties.

热软化效应对聚甲基丙烯酸甲酯刮擦变形定量模拟的影响

采用2种本构行为对聚甲基丙烯酸甲酯(PMMA)刮擦变形进行有限元模拟。结果表明,对PMMA而言,在模拟过程中若忽略屈服点后的热软化现象,则会导致刮擦模拟结果与实验结果产生较大偏差。但同时也发现,若在模拟时采用高速压缩测试获得的结果对PMMA刮擦过程中屈服点后的热软化进行描述,会导致刮擦模拟结果与实验结果产生更大的偏差。进一步分析表明,这是由于常规高速压缩测试过程中的温度上升幅度远大于刮擦形变所导致的。高速压缩测试需要采用厚度为0.06~0.10 mm的PMMA样品,其获得的结果才能实现更为准确的刮擦模拟。但当前的高速压缩测试技术只能使用较厚的样品(毫米级)进行测试,使用更薄的样品尚不具有可行性。

Research and application of a power-flow-calculation method in multiterminal VSC-HVDC power grid

For demonstrating a multiterminal voltage-source converter(VSC)-based high-voltage DC(HVDC)(VSCHVDC) project, this study puts forward a technical route for calculating the power flow in a 500-kV VSC-HVDC power grid in comparison with that of an AC power grid. The Jacobian matrix used in the power-flow calculation was deduced through methods such as Newton–Laphson iteration and Taylor series expansion. Further, the operation effect of powerflow calculation on a true bipolar VSC-HVDC power grid was analyzed briefly. The elements of the Jacobian matrix corresponding to VSC were studied under the mode of droop control and the control strategy of VSC-HVDC power grid was analyzed in detail. The power-flow calculation model for VSC-HVDC power grid of the master–slave control mode was simplified using the PQ decomposition method of the power-flow calculation of an AC power grid. Moreover, a four-terminal model of the Zhangbei VSC-HVDC demonstration project was established and tested on MATLAB. The simulation results under two kinds of operating conditions were analyzed and compared to the results of BPA; the deviation between the power-flow results was studied. The results show that the proposed calculation method can provide a feasible support for calculating the power flow in VSC-HVDC grids.

Generalized Parallel Coprime Array for Two-Dimensional DOA Estimation:A Perspective from Maximizing Degree of Freedom

Parallel arrays with coprime subarrays have shown its potential advantages for two dimensional direction of arrival(DOA)estimation.In this paper,by introducing two flexible coprime factors to enlarge the inter-element spacing of parallel uniform subarrays,we propose a generalized parallel coprime array(GPCA)geometry.The proposed geometry enjoys flexible array layouts by the coprime factors and enables to extend the array aperture to achieve great improvement of estimation performance.Meanwhile,we verify that GPCA always can obtain M2 degrees of freedom(DOFs)in co-array domain via 2M sensors after optimization,which outperforms sparse parallel array geometries,such as parallel coprime array(PCA)and parallel augmented coprime array(PACA),and is the same as parallel nested array(PNA)with extended aperture.The superiority of GPCA geometry has been proved by numerical simulations with sparse representation methods.

Edge Semantic Cognitive Intelligence for 6G Networks:Novel Theoretical Models,Enabling Framework,and Typical Applications

Edge intelligence is anticipated to underlay the pathway to connected intelligence for 6G networks,but the organic confluence of edge computing and artificial intelligence still needs to be carefully treated.To this end,this article discusses the concepts of edge intelligence from the semantic cognitive perspective.Two instructive theoretical models for edge semantic cognitive intelligence(ESCI)are first established.Afterwards,the ESCI framework orchestrating deep learning with semantic communication is discussed.Two representative applications are present to shed light on the prospect of ESCI in 6G networks.Some open problems are finally listed to elicit the future research directions of ESCI.

Multiple Emitters Localization by UAV with Nested Linear Array:System Scheme and 2D-DOA Estimation Algorithm

Unmanned Aerial Vehicle(UAV)equipped with uniform linear array has been applied to multiple emitters localization.Meanwhile,nested linear array enables to enhance localization resolution and achieve under-determined Direction of Arrival(DOA)estimation.In this paper,we propose a new system structure for emitters localization that combines the UAV with nested linear array,which is capable of significantly increasing the positioning accuracy of interested targets.Specifically,a localization scheme is designed to obtain the paired two-dimensional DOA(2D-DOA,i.e.azimuth and elevation angles)estimates of emitters by nested linear array with UAV.Furthermore,we propose an improved DOA estimation algorithm for emitters localization that utilizes Discrete Fourier Transform(DFT)method to obtain coarse DOA estimates,subsequently,achieve the fine DOA estimates by sparse representation.The proposed algorithm has lower computational complexity because the coarse DOA estimates enable to shrink the range of over-complete dictionary of sparse representation.In addition,compared to traditional uniform linear array,improved 2D-DOA estimation performance of emitters can be obtained with a nested linear array.Extensive simulation results testify the effectiveness of the proposed method.

Blind channel estimation for multiple antenna OFDM system subject to unknown carrier frequency offset

The problem of channel estimation for multiple an- tenna orthogonal frequency division multiplexing （OFDM） systems subject to unknown carrier frequency offset （CFO） is addressed. Multiple signal classification （MUSIC）-Iike algorithm, which generally has been used for direction estimation or frequency estimation, is used for channel estimation in multiple antenna OFDM systems. A reduced dimensional （RD）-MUSIC based algorithm for channel estimation is proposed in multiple antenna OFDM systems with unknown CFO. The Cramer-Rao bound （CRB） of channel estimation in multiple antenna OFDM systems with unknown CFO is derived. The proposed algorithm has a superior performance of channel estimation compared with the Capon method and the least squares method.

Weaker Interactions in Zn^(2+)and Organic Ion-pre-intercalated Vanadium Oxide toward Highly Reversible Zinc-ion Batteries

Driven by safety issues,environmental concerns,and high costs,rechargeable aqueous zinc-ion batteries(ZIBs)have received increasing attention in recent years owing to their unique advantages.However,the sluggish kinetics of divalent charge Zn^(2+)in the cathode materials caused by the strong electrostatic interaction and their unsatisfactory cycle life hinder the development of ZIBs.Herein,organic cations and Zn^(2+)ions co-pre-inserted vanadium oxide([N(CH_(3))_(4)]_(0.77),Zn_(0.23))V_(8)O_(20)·3.8H_(2)O are reported as the cathode for ultra-stable aqueous ZIBs,in which the weaker electrostatic interactions between Zn^(2+)and organic ion-pinned vanadium oxide can induce the high reversibility of Zn^(2+)insertion and extraction,thereby improving the cycle life.It is demonstrated that([N(CH_(3))_(4)]_(0.77),Zn_(0.23))V_(8)O_(20)·3.8H_(2)O cathodes deliver a discharge capacity of 181 mA h g^(-1)at8 A g^(-1)and ultra-long life span(99.5%capacity retention after 2000 cycles).A reversible Zn^(2+)/H^(+)ions(de)intercalation storage process and pseudocapacitive charge storage are characterized.The weaker interactions between organic ion and Zn^(2+)open a novel avenue for the design of highly reversible cathode materials with long-term cycling stability.

Bond Behavior between BFRP Bars and Hybrid Fiber Recycled Aggregate Concrete after High Temperature

The aim of this study is to improve the bond performance of basalt fiber reinforced polymer(BFRP)bars and recycled aggregate concrete(RAC)after being exposed to high temperatures.The bond behavior(failure modes,bond strength,bond stress-slip curves)between BFRP bars and hybrid fiber recycled aggregate concrete(HFRAC)after being exposed to temperatures ranging from 20℃up to 500℃was studied by using pull-out tests.The effect of high temperatures on mechanical properties of concrete(compressive strength,splitting tensile strength)and tensile strength of BFRP bars was also investigated.The bond strength decreased as the temperature increased and the drop of bond strength between RAC and BFRP bar was larger than that between HFRAC and BFRP bar.As the temperature rises,the key factor affecting the bond strength was gradually transformed from concrete strength to BFRP bar strength.The relationship between bond stress and slip in the dimensionless bond stress-slip ascending section was established,which was in good agreement with the experimental results.

GROWTH AND DISTORTION THEOREMS FOR ALMOST STARLIKE MAPPINGS OF COMPLEX ORDER λ

In this article, the sharp growth theorem for almost starlike mappings of complex order λ is given firstly. Secondly, distortion theorem along a unit direction is also established as the application of the growth theorem. In particular, using our results can reduce to some well-known results.

Adaptive Control of Discrete-time Nonlinear Systems Using ITF-ORVFL

Random vector functional ink(RVFL)networks belong to a class of single hidden layer neural networks in which some parameters are randomly selected.Their network structure in which contains the direct links between inputs and outputs is unique,and stability analysis and real-time performance are two difficulties of the control systems based on neural networks.In this paper,combining the advantages of RVFL and the ideas of online sequential extreme learning machine(OS-ELM)and initial-training-free online extreme learning machine(ITFOELM),a novel online learning algorithm which is named as initial-training-free online random vector functional link algo rithm(ITF-ORVFL)is investigated for training RVFL.The link vector of RVFL network can be analytically determined based on sequentially arriving data by ITF-ORVFL with a high learning speed,and the stability for nonlinear systems based on this learning algorithm is analyzed.The experiment results indicate that the proposed ITF-ORVFL is effective in coping with nonparametric uncertainty.

A cohort study of adolescents with depression in China:tracking multidimensional outcomes and early biomarkers for intervention

Background Depression in adolescents is recognised as a global public health concern,but little is known about the trajectory of its clinical symptoms and pathogenesis.Understanding the nature of adolescents with depression and identifying earlybiomarkers can facilitatepersonalised intervention andreducediseaseburden.Aims To track multidimensional outcomes of adolescents with depression and develop objective biomarkers for diagnosis,as well as response to treatment,prognosis and guidance for early identification and intervention.Methods This is a multidimensional cohort study on the Symptomatic trajectory and Biomarkers of Early Adolescent Depression(sBEAD).We planned to recruit more than 1000 adolescents with depression and 300 healthy controls within 5 years.Multidimensional clinical presentations and objective indicators are collected at baseline,weeks 4,8,12 and 24,and years 1,2,3,4 and 5.Conclusions To the best of our knowledge,this is the first longitudinal cohort study that examines multidimensional clinical manifestations and multilevel objective markers in Chinese adolescents with depression.This study aims at providing early individualised interventions for young,depressed patients to reduce the burden of disease.