The Influence of Arctic Sea Ice Concentration Perturbations on Subseasonal Predictions of North Atlantic Oscillation Events

The influence of Arctic sea ice concentration (SIC) on the subseasonal prediction of the North Atlantic Oscillation (NAO) event is investigated by utilizing the Community Atmospheric Model version 4. The optimal Arctic SIC perturbations which exert the greatest influence on the onset of an NAO event from a lead of three pentads (15 days) are obtained with a conditional nonlinear optimal perturbation approach. Numerical results show that there are two types of optimal Arctic SIC perturbations for each NAO event, with one weakening event (marked as type-1) and another strengthening event (marked as type-2). For positive NAO events, type-1 optimal SIC perturbations mainly show positive SIC anomalies in the Greenland, Barents, and Okhotsk Seas, while type-2 perturbations mainly feature negative SIC anomalies in these regions. For negative NAO events, the optimal SIC perturbations have almost opposite patterns to those in positive events, although there are some differences among these SIC perturbations due to different atmospheric initial conditions. Further diagnosis reveals that the optimal Arctic SIC perturbations first modify the surface turbulent heat flux and the temperature in the lower troposphere via diabatic processes. Afterward, the temperature in the low troposphere is mainly affected by dynamic advection. Finally, potential vorticity advection plays a crucial role in the 500-hPa geopotential height prediction in the northern North Atlantic sector during pentad 4, which influences NAO event prediction. These results highlight the importance of Arctic SIC on NAO event prediction and the spatial characteristics of the SIC perturbations may provide scientific support for target observations of SIC in improving NAO subseasonal predictions.

Influence of Arctic Sea-ice Concentration on Extended-range Forecasting of Cold Events in East Asia

Utilizing the Community Atmosphere Model,version 4,the influence of Arctic sea-ice concentration(SIC)on the extended-range prediction of three simulated cold events(CEs)in East Asia is investigated.Numerical results show that the Arctic SIC is crucial for the extended-range prediction of CEs in East Asia.The conditional nonlinear optimal perturbation approach is adopted to identify the optimal Arctic SIC perturbations with the largest influence on CE prediction on the extended-range time scale.It shows that the optimal SIC perturbations are more inclined to weaken the CEs and cause large prediction errors in the fourth pentad,as compared with random SIC perturbations under the same constraint.Further diagnosis reveals that the optimal SIC perturbations first modulate the local temperature through the diabatic process,and then influence the remote temperature by horizontal advection and vertical convection terms.Consequently,the optimal SIC perturbations trigger a warming center in East Asia through the propagation of Rossby wave trains,leading to the largest prediction uncertainty of the CEs in the fourth pentad.These results may provide scientific support for targeted observation of Arctic SIC to improve the extended-range CE prediction skill.

Study on the Antioxidation of the Compound Beverage of Winter Jujube and Peanut Meal

[Objective]The aim was to study the antioxidative index of the compound beverage of winter jujube and peanut meal,discuss the impact of the storage conditions on its antioxidative activity and provide theoretical basis for the utilization of winter jujube and peanut meal resources.[Method]A kind of compound beverage was prepared with winter jujube and peanut meal,and its antioxidative activity was detected and its best storage conditions were determined.[Result]The capacity of the compound beverage stored for 20 d to scavenge·OH,DPPH·and nitroso was the highest at freeze conditions,then followed by the refrigeration conditions,room temperature storage and sunlight.The total reducing capacity of the products was the highest under freezing conditions while the lowest under sunlight when some active components were destroyed.[Conclusion]It is the best to store the compound beverage of winter jujube and peanut meal at freeze conditions and better at the refrigeration conditions.The storage of compound beverage should avoid direct sunlight.

Synthesis and Adsorption Properties of Chelating Resins Containing Sulfoxide and Heterocyclic Functional Groups

Several of new chelating resins containing sulfoxide and heterocyclic functional groups （3-aminopyridine and 2-mercaptobenzothiazole） based on macroporous chloromethylated polystyrene were synthesized and characterized by elemental analysis and infrared spectra. Their adsorption capacities towards Zn^2＋, Cu^2＋, Pb^2＋, Hg^2＋ and Ag^＋ at pH 3.0 and 6.0 were investigated in detail. It was found that the adsorption capacities of the resins containing bis[（3-pyridylaminoethyl）sulfoxide or （2-benzothiazolylthioethyl）sulfoxide for the above ions were higher than that on ones containing single above-mentioned groups.

Fully Differential Leapfrog Implementation for High-Pass Ladder Filters

This paper presents a novel leapfrog signal flow graph (SFG) implementation by fully differential Op amp integrators, which combines low sensitivity, high dynamic range with simple circuit configuration. The direct SFG simulation and leapfrog SFG simulation can yield integrator-based structures likewise, but both of them will lead to higher circuit complexity, noise density and sensitivity. Three Butterworth 5-order high-pass filters with a pass band edge frequency of 1.778 kHz are designed based on different SFGs. From the example, the noise density of the simplest leapfrog configuration is approximately 0.4 nV/Hz1/2 lower than those of the other two in the stop band, and shows the best noise density in the pass band. The sensitivity densities of two types of leapfrog filters are approximately equivalent, while that of the direct SFG simulation filter is much higher. However, the pass band response of the simplest configuration is not as good as those of the other two because of two parasitic zeros (at 708 kHz, -31.6 dB and 1.59 MHz, -20.55 dB) and a parasitic pole (at 4.57 MHz, 45.5 dB).

High-Resolution Traffic Flow Prediction Model Based on Deep Learning

The time resolution of the existing traffic flow prediction model is too big to be applied to adaptive signal timing optimization.Based on the view of the platoon dispersion model,the relationship between vehicle arrival at the downstream intersection and vehicle departure from the upstream intersection was analyzed.Then,a high-resolution traffic flow prediction model based on deep learning was developed.The departure flow rate from the upstream and the arrival flow rate at the downstream intersection was taking as the input and output in the proposed model,respectively.Finally,the parameters of the proposed model were trained by the field data,and the proposed model was implemented to forecast the arrival flow rate of the downstream intersection.Results show that the proposed model can better capture the fluctuant traffic flow and reduced MAE,MRE,and RMSE by 9.53%,39.92%,and 3.56%,respectively,compared with traditional models and algorithms,such as Robert­son's model and artificial neural network.Therefore,the proposed model can be applied for realtime adaptive signal timing optimization.

Modeling,Identification and Simulation of DC Resistance Spot Welding Process for Aluminum Alloy 5182

Currently the aluminum alloy resistance spot welding(AA-RSW) has been extensively used for light weight automotive body-in-white manufacturing.However the aluminum alloys such as AA5182 have inferior weldability for forming the joint due to their high reflectiveness to heat and light.Therefore it is necessary to further develop the high performance control strategy and the set-up of a new welding schedule.The welding process identification is the essential issue where the difficulty arises from the fact that the AA-RSW is a nonlinear time-varying uncertain process which couples the thermal,electrical,mechanical and metallurgical dynamics.To understand this complicated physical phenomenon a novel dual-phase M-series pseudo-random electrical pattern is adopted to excite the AA-RSW electrical-thermal process and the thermal response is recorded according to the welding power outputs.Based on the experimental information,the transfer function of an AA-RSW electrical- thermal mechanism is identified,and the optimum model order and parameters are determined.Subsequently a control-oriented DC AA-RSW model is established to explore the welding power control algorithm.The simulated results of the control model show agreement with the experimental data,which validates its feasibility for the corresponding welding control.

Research on dynamic load balancing of data flow under big data platform

In the big data platform,because of the large amount of data,the problem of load imbalance is prominent.Most of the current load balancing methods have problems such as high data flow loss rate and long response time;therefore,more effective load balancing method is urgently needed.Taking HBase as the research subject,the study analyzed the dynamic load balancing method of data flow.First,the HBase platform was introduced briefly,and then the dynamic load-balancing algorithm was designed.The data flow was divided into blocks,and then the load of nodes was predicted based on the grey prediction GM(1,1)model.Finally,the load was migrated through the dynamic adjustable method to achieve load balancing.The experimental results showed that the accuracy of the method for load prediction was high,the average error percentage was 0.93%,and the average response time was short;under 3000 tasks,the response time of the method designed in this study was 14.17%shorter than that of the method combining TV white space(TVWS)and long-term evolution(LTE);the average flow of nodes with the largest load was also smaller,and the data flow loss rate was basically 0%.The experimental results show the effectiveness of the proposed method,which can be further promoted and applied in practice.