Simultaneous Identification of Thermophysical Properties of Semitransparent Media Using a Hybrid Model Based on Artificial Neural Network and Evolutionary Algorithm

A hybrid identification model based on multilayer artificial neural networks(ANNs) and particle swarm optimization(PSO) algorithm is developed to improve the simultaneous identification efficiency of thermal conductivity and effective absorption coefficient of semitransparent materials.For the direct model,the spherical harmonic method and the finite volume method are used to solve the coupled conduction-radiation heat transfer problem in an absorbing,emitting,and non-scattering 2D axisymmetric gray medium in the background of laser flash method.For the identification part,firstly,the temperature field and the incident radiation field in different positions are chosen as observables.Then,a traditional identification model based on PSO algorithm is established.Finally,multilayer ANNs are built to fit and replace the direct model in the traditional identification model to speed up the identification process.The results show that compared with the traditional identification model,the time cost of the hybrid identification model is reduced by about 1 000 times.Besides,the hybrid identification model remains a high level of accuracy even with measurement errors.

Deactivation mechanism of acetone to isobutene conversion over Y/Beta catalyst

The conversion of acetone derived from biomass to isobutene has attracted extensive attentions.In comparison with Brønsted acidic catalyst,Lewis acidic catalyst could exhibit a better catalytic performance with a higher isobutene selectivity.However,the catalyst stability remains a key problem for the long-running acetone conversion and the reasons for catalyst deactivation are poorly understood up to now.Herein,the deactivation mechanism of Lewis acidic Y/Beta catalyst during the acetone to isobutene conversion was investigated by various characterization techniques,including acetone-temperature-programmed surface reaction,gas chromatography-mass spectrometry,in situ ultraviolet-visible,and ^(13)C cross polarization magic angle spinning nuclear magnetic resonance spectroscopy.A successive aldol condensation and cyclization were observed as the main side-reactions during the acetone conversion at Lewis acidic Y sites.In comparison with the low reaction temperature,a rapid formation and accumulation of the larger cyclic unsaturated aldehydes/ketones and aromatics could be observed,and which could strongly adsorb on the Lewis acidic sites,and thus cause the catalyst deactivation eventually.After a simple calcination,the coke deposits could be easily removed and the catalytic activity could be well restored.

Stochastic Air Traffic Flow Management for Demand and Capacity Balancing Under Capacity Uncertainty

This paper introduces an innovative approach to the synchronized demand-capacity balance with special focus on sector capacity uncertainty within a centrally controlled collaborative air traffic flow management(ATFM)framework.Further with previous study,the uncertainty in capacity is considered as a non-negligible issue regarding multiple reasons,like the impact of weather,the strike of air traffic controllers(ATCOs),the military use of airspace and the spatiotemporal distribution of nonscheduled flights,etc.These recessive factors affect the outcome of traffic flow optimization.In this research,the focus is placed on the impact of sector capacity uncertainty on demand and capacity balancing(DCB)optimization and ATFM,and multiple options,such as delay assignment and rerouting,are intended for regulating the traffic flow.A scenario optimization method for sector capacity in the presence of uncertainties is used to find the approximately optimal solution.The results show that the proposed approach can achieve better demand and capacity balancing and determine perfect integer solutions to ATFM problems,solving large-scale instances(24 h on seven capacity scenarios,with 6255 flights and 8949 trajectories)in 5-15 min.To the best of our knowledge,our experiment is the first to tackle large-scale instances of stochastic ATFM problems within the collaborative ATFM framework.

BiOCl-Bi12O17Cl2 nanocomposite with high visible-light photocatalytic activity prepared by an ultrasonic hydrothermal method for removing dye and pharmaceutical

A BiOCl-Bi12O17Cl2 nanocomposite with a high visible-light response and a low photoinduced electron-hole pair recombination rate was successfully synthesized using an ultrasonic-hydrothermal method.The texture,structure,optical,and photocatalytic properties of the composite were characterized.The results showed that the composite had a sheet flower-like structure with a large specific surface area.Ultraviolet-visible diffuse reflection spectra and photoluminescence spectra showed that the composite had an excellent visible-light response and a low recombination rate of photoinduced electron hole pairs.The photocatalytic property of the composite was evaluated by the removal efficiency of rhodamine B and ciprofloxacin under visible-light illumination.The composite’s reaction rate constant of removing rhodamine B(/ciprofloxacin)was approximately 8.14(/4.94),42.63(/11.91)and 64.66(/36.07)times that of Bi12O17Cl2,P25,and BiOCl,respectively.Furthermore,the composite showed a wide applicable pH range and excellent reusability.Mechanism analysis showed that photogenerated holes played a dominant role and·O2–also contributed to photocatalytic degradation.In summary,this study presents a high-efficiency photocatalyst for wastewater treatment.

Prediction of Departure Aircraft Taxi Time Based on Deep Learning

With the continuous increase in the number of flights,the use of airport collaborative decision-making(ACDM)systems has been more and more widely spread.The accuracy of the taxi time prediction has an important effect on the A-CDM calculation of the departure aircraft’s take-off queue and the accurate time for the aircraft blockout.The spatial-temporal-environment deep learning(STEDL)model is presented to improve the prediction accuracy of departure aircraft taxi-out time.The model is composed of time-flow sub-model(airport capacity,number of taxiing aircraft,and different time periods),spatial sub-model(taxiing distance)and environmental sub-model(weather,air traffic control,runway configuration,and aircraft category).The STEDL model is used to predict the taxi time of departure aircraft at Hong Kong Airport and the results show that the STEDL method has a prediction accuracy of 95.4%.The proposed model also greatly reduces the prediction error rate compared with the other machine learning methods.

Aviation Accident Causation Analysis Based on Complex Network Theory

Accident causation analysis is of great importance for accident prevention.In order to improve the aviation safety,a new analysis method of aviation accident causation based on complex network theory is proposed in this paper.Through selecting 257 accident investigation reports,45 causative factors and nine accident types are obtained by the three-level coding process of the grounded theory,and the interaction of these factors is analyzed based on the“2-4”model.Accordingly,the aviation accident causation network is constructed based on complex network theory which has scale-free characteristics and small-world properties,the characteristics of causative factors are analyzed by the topology of the network,and the key causative factors of the accidents are identified by the technique for order of preference by similarity to ideal solution(TOPSIS)method.The comparison results show that the method proposed in this paper has the advantages of independent of expert experience,quantitative analysis of accident causative factors and statistical analysis of a lot of accident data,and it has better applicability and advancement.

Influential Node Ranking and Invulnerability of Air Traffic Cyber Physical System

To ensure flight safety,the complex network method is used to study the influence and invulnerability of air traffic cyber physical system(CPS)nodes.According to the rules of air traffic management,the logical coupling relationship between routes and sectors is analyzed,an air traffic CPS network model is constructed,and the indicators of node influence and invulnerability are established.The K-shell algorithm is improved to identify node influence,and the invulnerability is analyzed under random and selective attacks.Taking Airspace in Eastern China as an example,its influential nodes are sorted by degree,namely,K-shell,the improved K-shell(IKS)and betweenness centrality.The invulnerability of air traffic CPS under different attacks is analyzed.Results show that IKS can effectively identify the influential nodes in the air traffic CPS network,and IKS and betweenness centrality are the two key indicators that affect the invulnerability of air traffic CPS.

Effects of Social Security Spending on Income Distribution and Poverty Reduction in China

Reasonable income distribution and eradication of rural poverty are vital for building a moderately prosperous society in all respects in China.This paper primarily examines the income distribution and poverty reduction effects of social security spending.Market income and redistribution policies are two determinants of income gaps.Based on CHIP2018 household survey data,we find that inadequate income redistribution policies have contributed to yawning income gaps,and that social security spending is more redistributive than personal income tax and social security contributions.After estimating the redistribution effects of social security spending and itemized incomes,we find that pension payments have contributed the most to household income gaps,and that subsistence protection and rural pension payments help improve income distribution.With respect to the poverty reduction effects of social security spending,we have estimated China’s current poverty incidence and the poverty reduction effects of pension payments,healthcare,and educational allowances with CHIP2018 data,and discover that an increase in social security spending may effectively reduce rural poverty.In building a moderately prosperous society in all respects,China should increase social security spending,focusing on specific target groups,and promote the role of social security spending in regulating income distribution and offering social protection to rural residents.

Highly selective acetone sensor based on ternary Au/Fe_2O_3-ZnO synthesized via co-precipitation and microwave irradiation

Ternary Au/Fe2O3-ZnO gas-sensing materials were synthesized by combining co-precipitation and microwave irradiation process.The as-prepared Au/Fe2O3-ZnO was characterized with X-ray diffractometer and scanning electron microscope,and its gas-sensing performance was measured using a gas-sensor analysis system.The results show that the as-prepared products consist of hexagonal wurtzite ZnO,face-centered cubic gold nanoparticles and orthorhombic Fe2O3crystallines.The Au/Fe2O3-ZnO based sensor has a very high selectivity to ethanol and acetone,and also has high sensitivity(154)at a low working temperature(270°C)and an extremely fast response(1s)against acetone.It is found that the selectivity can be adjusted by Fe2O3content added in the ternary materials.It possesses a worth looking forward prospect to practical applications in acetone detecting and administrating field.

China’s Economic Growth and High-Quality Development:2020-2035

The time period between 2020 and 2035 is vital for China to achieve its second centennial goal.During this period,China must avoid the middle-income trap and achieve socialist modernization.To accomplish this goal,China must maintain a certain pace of economic growth and strive to double its real GDP per capita by 2035.However,by the current growth trajectory,China’s average economic growth rate is expected to stay at approximately 3.8%over the period between 2020-2035.This makes the GDP per capita growth target hard to achieve.Even when in a high-quality development stage,China should speed up economic growth while enhancing growth quality.Speed and quality are interdependent rather than contradictory with each other.To ramp up economic growth potentials,China must proceed with market-oriented reforms and shift economic growth drivers.To improve economic growth quality,household consumption should be increased to unleash China’s full potential,not only as the factory floor of the world but also one of world’s biggest markets,i.e.“dual circulations.”With appropriate policy response,China’s economy will be poised to achieve the goal of doubling real GDP per capita by 2035,marking a large stride in its economic aggregate and urban and rural household per capita incomes.

Cause Analysis of Consumer‑Grade UAV Accidents Based on Grounded Theory‑Bayesian Network

In order to reduce the accident rate of consumer-grade unmanned aerial vehicles(UAVs)in daily use scenarios,the accident causes are analyzed based on the accident cases of consumer-grade UAVs.By extracting accident causing factors based on the Grounded theory,the relationship between these factors is analyzed.The Bayesian network for consumer-grade UAV accidents is constructed.With the Grounded theory-Bayesian network,the probability of four types of accidents is inferred:fall,air collision,disappearance,and personal injury.With the posterior probability of each factor being reversely reasoned,the causal chain with the maximum probability of each accident is obtained.After the sensitivity of each factor is analyzed,the key nodes in the network accordingly are inferred.Then the causing factors of consumer-grade UAV accidents are analyzed.The results show that the probability of fall accident is the highest,the fall accident is associated with the probabilistic maximum causal chain of personal injury,and the sensitivity analysis results of each type of accident as the result node are inconsistent.

Social Security Development in China and Its Support to Economic Transition

In 70 years since the founding of the People’s Republic of China,China has successfully transitioned from a closed economy to an open economy with the watershed year of reform and opening up in 1978 and modernized its social security system accordingly.This paper divides the transition of China’s social security system into seven stages before and after 1978.The traditional social security system was predicated on the dominant public ownership,a highly centralized economy,and“full employment.”It was congruous with the ownership structure,income distribution,and labor systems under the closed economy.The modern social security system is developed to meet the needs of an open economy and promotes economic development by giving play to consumption and investment,facilitating labor flow,and boosting productivity.The modern social security system requires further supply-side structural reforms to promote the high-quality development of the open economy.

The effect of cations(NH_4^+,Na^+,K^+,and Ca^(2+)) on chemical deactivation of commercial SCR catalyst by bromides

Alkali and alkaline‐earth metals from fly ash have a significant deactivation effect on catalysts used for selective catalytic reduction of NOx by NH3(NH3‐SCR).Bromides are considered effective additives to improve Hg0 oxidation on SCR catalysts.In this work,the effects of different bromides(NH4Br,NaBr,KBr,and CaBr2)on a commercial V2O5‐WO3/TiO2 catalyst were studied.NOx conversion decreased significantly over the KBr‐poisoned catalyst(denoted as L‐KBr),while that over NaBr‐and CaBr2‐poisoned catalysts(denoted as L‐NaBr and L‐CaBr,respectivity)decreased to a lesser extent compared with the fresh sample.Poor N2 selectivity was observed over L‐NaBr,L‐KBr and L‐CaBr catalysts.The decrease in the ratio of chemisorbed oxygen to total surface oxygen(Oα/(Oα+Oβ+Ow)),reducibility and surface acidity might contribute to the poor activity and N2 selectivity over L‐KBr catalyst.The increased Oαratio was conducive to the enhanced reducibility of L‐CaBr.Combined with enhanced surface acidity,this might offset the negative effect of the loss of active sites by CaBr2 covering.The overoxidation of NH3 and poor N2 selectivity in NH3 oxidation should retard the SCR activity at high temperatures over L‐CaBr catalyst.The increased basicity might contribute to increased NOx adsorption on L‐KBr and L‐CaBr catalysts.A correlation between the acid‐basic and redox properties of bromide‐poisoned catalysts and their catalytic properties is established.

An Air Route Planning Model of Unmanned Aerial Vehicles Under Constraints of Ground Safety

With the rapid growth of the number and flight time of unmanned aerial vehicles(UAVs),safety accidents caused by UAVs flight risk is increasing gradually.Safe air route planning is an effective means to reduce the operational risk of UAVs at the strategic level.The optimal air route planning model based on ground risk assessment is presented by considering the safety cost of UAV air route.Through the rasterization of the ground surface under the air route,the safety factor of each grid is defined with the probability of fatality on the ground per flight hour as the quantitative index.The air route safety cost function is constructed based on the safety factor of each grid.Then,the total cost function considering both air route safety and flight distance is established.The expected function of the ant colony algorithm is rebuilt and used as the algorithm to plan the air routes.The effectiveness of the new air route planning model is verified through the logistical distribution scenario on urban airspace.The results indicate that the new air route planning model considering safety factor can greatly improve the overall safety of air route under small increase of the total flight time.

Empirical Exploration of Air Traffic Control Behaviour at Terminal Maneuvering Area:From an Air Traffic Flow Aspect

In a large-volume,high-density traffic background,air traffic manifests fluid-like microscopical characteristics.The characteristics are formed by the micro tailing actions between individual aircraft.Aircraft headway refers to the time interval between successive flying aircraft in air traffic flow,which is one of the most important characteristics of air traffic flow.The variation in aircraft headway reveals the air traffic control behaviour.In this paper,we study the characteristics of air traffic control behaviours by analyzing radar tracks in a terminal maneuvering area.The headway in arrival traffic flow is measured after the determination of aircraft trailing relationships.The headway evolutionary characteristics for different control decisions and the headway evolutionary characteristics in different phase-states are discussed,and some interesting findings are gotten.This work may be helpful for scholars and managers in understanding the intrinsic nature of air traffic flow and in the development of intelligent assistant decision systems for air traffic management.

A Novel Deep Neural Network Compression Model for Airport Object Detection

A novel deep neural network compression model for airport object detection has been presented.This novel model aims at disadvantages of deep neural network,i.e.the complexity of the model and the great cost of calculation.According to the requirement of airport object detection,the model obtains temporal and spatial semantic rules from the uncompressed model.These spatial semantic rules are added to the model after parameter compression to assist the detection.The rules can improve the accuracy of the detection model in order to make up for the loss caused by parameter compression.The experiments show that the effect of the novel compression detection model is no worse than that of the uncompressed original model.Even some of the original model false detection can be eliminated through the prior knowledge.

Mononuclear first-row transition-metal complexes as molecular catalysts for water oxidation

Water oxidation is significant in both natural and artificial photosynthesis.In nature,water oxidation occurs at the oxygen‐evolving center of photosystem II,and leads to the generation of oxygen,protons,and electrons.The last two are used for fixation of carbon dioxide to give carbohydrates.In artificial processes,the coupling of water oxidation to evolve O2and water reduction to evolve H2is known as water splitting,which is an attractive method for solar energy conversion and storage.Because water oxidation is a thermodynamically uphill reaction and is kinetically slow,this reaction causes a bottleneck in large‐scale water splitting.As a consequence,the development of new and efficient water oxidation catalysts(WOCs)has attracted extensive attention.Recent efforts have identified a variety of mononuclear earth‐abundant transition‐metal complexes as active and stable molecular WOCs.This review article summarizes recent progress in research on mononuclear catalysts that are based on first‐row transition‐metal elements,namely manganese,iron,cobalt,nickel,and copper.Particular attention is paid to catalytic mechanisms and the key O?O bond formation steps.This information is critical for designing new catalysts that are highly efficient and stable.

Finite Element Modeling and Parametric Analysis of Pavement Dynamic Responses under Moving Vehicle Load

This paper intends to develop finite element models that can simulate vehicle load moving on pavement system and reflect the pavement response of vehicle and pavement interaction.We conduct parametric analysis considering the influences of asphalt concrete layer modulus and thickness,base layer modulus and thickness,and subgrade modulus on pavement surface displacement,frequency,and strain response.The analysis findings are fruitful.Both the displacement basin width and maximum value of dynamic surface displacements are larger than those of static surface displacements.The frequency is positively correlated with the pavement structure moduli,and negatively correlated with the pavement structure thicknesses.The shape of dynamic and static tensile strain is similar along the depth of the pavement structure.The maximum value of dynamic tensile strain is larger than that of static tensile strain.The frequency of entire pavement structure holds more significant influence than the surface displacement and strain do.The subgrade modulus has a significant effect on surface displacement,frequency and strain.

SA-FRCNN:An Improved Object Detection Method for Airport Apron Scenes

The airport apron scene contains rich contextual information about the spatial position relationship.Traditional object detectors only considered visual appearance and ignored the contextual information.In addition,the detection accuracy of some categories in the apron dataset was low.Therefore,an improved object detection method using spatial-aware features in apron scenes called SA-FRCNN is presented.The method uses graph convolutional networks to capture the relative spatial relationship between objects in the apron scene,incorporating this spatial context into feature learning.Moreover,an attention mechanism is introduced into the feature extraction process,with the goal to focus on the spatial position and key features,and distance-IoU loss is used to achieve a more accurate regression.The experimental results show that the mean average precision of the apron object detection based on SAFRCNN can reach 95.75%,and the detection effect of some hard-to-detect categories has been significantly improved.The proposed method effectively improves the detection accuracy on the apron dataset,which has a leading advantage over other methods.

En-route Sector Complexity Control Strategies in Air Traffic Management

Along with the rapid development of air traffic, the contradiction between conventional air traffic management(ATM)and the increasingly complex air traffic situations is more severe,which essentially reduces the operational efficiency of air transport systems. Thus,objectively measuring the air traffic situation complexity becomes a concern in the field of ATM. Most existing studies focus on air traffic complexity assessment,and rarely on the scientific guidance of complex traffic situations. According to the projected time of aircraft arriving at the target sector boundary,we formulated two control strategies to reduce the air traffic complexity. The strategy of entry time optimization was applied to the controllable flights in the adjacent upstream sectors. In contrast,the strategy of flying dynamic speed optimization was applied to the flights in the target sector. During the process of solving complexity control models,we introduced a physical programming method. We transformed the multi-objective optimization problem involving complexity and delay to single-objective optimization problems by designing different preference function. Actual data validated the two complexity control strategies can eliminate the high-complexity situations in reality. The control strategy based on the entry time optimization was more efficient than that based on the speed dynamic optimization. A basic framework for studying air traffic complexity management was preliminarily established. Our findings will help the implementation of a complexity-based ATM.