COMPENSATION CONTROL OF REAL-TIME UNBALANCE FORCE FOR ACTIVE MAGNETIC BEARING SYSTEM

Aiming at the stability and others properties of active magnetic bearing （AMB） system influenced by the periodic unbalance stimulation synchronous with rotor rotational speed, a new real-time adaptive feed-forward unbalance force compensation scheme is proposed based on variable step-size least mean square（LMS） algorithm as the feed-forward compensation controller. The controller can provide some suitable sinusoidal signals to com- pensate the feedback unbalance response signals synchronous with the rotary frequency, then reduce the fluctua- tion of the control currents and weaken the active control of AMB system. The variable step-size proportional to the rotational frequency is deduced by analyzing the principle of normal LMS algorithm and its deficiency in the application of real-time filtering of AMB system. Experimental results show that the new method can implement real-time unbalance force compensation in a wide frequency band, reduce the effect of unbalance stimulant force on the housing of AMB system, and provide convenience to improve rotational speed.

PSA-based prostate cancer screening： the role of active surveillance and informed and shared decision making

Since the first publication describing the identification of prostate-specific antigen （PSA） in the 1960s, much progress has been made. The PSA test changed from being initially a monitoring tool to being also used as a diagnostic tool. Over time, the test has been heavily debated due to its lack of sensitivity and specificity. However, up to now the PSA test is still the only biomarker for the detection and monitoring of prostate cancer. PSA-based screening for prostate cancer is associated with a high proportion of unnecessary testing and overdiagnosis with subsequent overtreatment. In the early years of screening for prostate cancer, high rates of uptake were very important. However, over time the opinion on PSA-based screening has shifted towards the notion of informed choice. Nowadays, it is thought to be unethical to screen men without them being aware of the pros and cons of PSA testing, as well as the fact that an informed choice is related to better patient outcomes. Now, as the results of three major screening studies have been presented and the downsides of screening are becoming better understood, informed choice is becoming more relevant.

Modeling and Design of Real-Time Pricing Systems Based on Markov Decision Processes

A real-time pricing system of electricity is a system that charges different electricity prices for different hours of the day and for different days, and is effective for reducing the peak and flattening the load curve. In this paper, using a Markov decision process (MDP), we propose a modeling method and an optimal control method for real-time pricing systems. First, the outline of real-time pricing systems is explained. Next, a model of a set of customers is derived as a multi-agent MDP. Furthermore, the optimal control problem is formulated, and is reduced to a quadratic programming problem. Finally, a numerical simulation is presented.

Real-time Design Constraints in Implementing Active Vibration Control Algorithms

Although computer architectures incorporate fast processing hardware resources, high performance real-time implementation of a complex control algorithm requires an efficient design and software coding of the algorithm so as to exploit special features of the hardware and avoid associated architecture shortcomings. This paper presents an investigation into the analysis and design mechanisms that will lead to reduction in the execution time in implementing real-time control algorithms. The proposed mechanisms are exemplified by means of one algorithm, which demonstrates their applicability to real-time applications. An active vibration control （AVC） algorithm for a flexible beam system simulated using the finite difference （FD） method is considered to demonstrate the effectiveness of the proposed methods. A comparative performance evaluation of the proposed design mechanisms is presented and discussed through a set of experiments.

Real-Time Method for Detecting Harmonic and Reactive Currents of Single-Phase Circuits

According to the characteristics of single-phase circuits and demand of using active filter for real-time detecting harmonic and reactive currents, a detecting method based on Fryze＇s power definition is proposed. The results of theoretical analysis and simula- tion show that the proposed method is effective in realtime detecting of instantaneous harmonic and reactive currents in single-phase circuits. When only detecting the total reactive currents, this method does not need a phase-locked loop circuit, and it also can be used in some special applications to provide different compensations on the ground of different requirements of electric network. Compared with the other methods based on the theory of instantaneous reactive power, this method is simple and easy to realize.

Real-Time Detection of Unstable Control Loop Behavior in a Feedback Active Noise Cancellation System for In-Ear Headphones

Active noise controls are used in a wide field of applications to cancel out unwanted surrounding noise. Control systems based on the feedback structure however have the disadvantage that they may become unstable during run-time due to changes in the control path—in this context including the listener’s ear. Especially when applied to active noise cancellation (ANC) headphones, the risk of instability is associated with the risk of harmful influence on the listener’s ear, which is exposed to the speaker in striking distance. This paper discusses several methods to enable the analysis of a feedback ANC system during run-time to immediately detect instability. Finally, a solution is proposed, which identifies the open loop behavior parametrically by means of an adaptive filter to subsequently evaluate the coefficients regarding stability.

Intercross real-time control strategy in alternating activated sludge process for short-cut biological nitrogen removal treating domestic wastewater

To develop technically feasible and economically favorable dynamic process control(DPC)strategies for an alternating activated sludge(AAS)system,a bench-scale continuous-flow alternating aerobic and anoxic reactor,performing short-cut nitrogen removal from real domestic wastewater was operated under different control strategies for more than five months.A fixed-time control(FTC) study showed that bending-points on pH and oxidation-reduction potential(ORP)profiles accurately coincided with the major biologic...

Relationships between Features of EmergingAdulthood, Situated Decisions toward PhysicalActivity, and Physical Activity among CollegeStudents: The Moderating Role of ExerciseIntensity Tolerance

A significant portion of emerging adults do not achieve recommended levels of physical activity (PA). Previous studies observedassociations between features of emerging adulthood and PA levels, while the potential psychological mechanisms that mightexplain this phenomenon are not fully understood. In this context, there is some evidence that situated decisions towardphysical activity (SDPA) and exercise-intensity tolerance might influence PA level. To provide empirical support for thisassumption, the current study investigated whether (i) features of emerging adulthood are linked to SDPA, which, in turn,might affect PA engagement;(ii) exercise-intensity tolerance moderate the relationship between SDPA and PA level;and (iii)SDPA is a mediator of the relationship between features of emerging adulthood and PA levels under the prerequisite thatexercise-intensity tolerance moderates the link between SDPA and PA engagement. In this study a group of 1,706 Chinesecollege students was recruited and asked to complete a set of questionnaires assessing their SDPA, PA levels, exercise-intensitytolerance, and features associated with emerging adulthood, namely Self-exploration, Instability, and Possibility. Our resultsindicated that SDPA positively predicted PA levels and this relationship became stronger when exercise-intensity tolerance wasused as a moderator. Furthermore, it was observed that individuals with a higher level of Instability and a lower level ofPossibility during emerging adulthood exhibited a lower level of SDPA. Taken together, the results of our study providefurther insights on a potential psychological mechanism linking features of emerging adulthood and physical activity.

Optimal pricing decision model based on activity-based costing

In order to find out the applicability of the optimal pricing decision model based on conventional cost behavior model after activity based costing has given strong shock to the conventional cost behavior model and its assumptions, detailed analyses have been made using the activity based cost behavior and cost volume profit analysis model, and it is concluded from these analyses that the theory behind the construction of optimal pricing decision model is still tenable under activity based costing, but the conventional optimal pricing decision model must be modified as appropriate to the activity based costing based cost behavior model and cost volume profit analysis model, and an optimal pricing decision model is really a product pricing decision model constructed by following the economic principle of maximizing profit.

Electroencephalographic Activity Associated to Investment Decisions: Gender Differences

Literature in finance and neurosciences shows that male and female differ in many relevant issues concerning financial decision investment. Here, we studied the EEG activity recorded while volunteers were playing a stock trading game to investigate these gender differences. 20 males and 20 females made 100 trading decisions using a portfolio of 200 shares of 7 different companies. Males and females were equally successful in earning above the market. sLORETA was used to identify sources of EEG recorded 2 seconds before trading decision. Results showed that male and female used different sets of neuron to make equally successful financial decisions.

Safety-assured,real-time neural active fault management for resilient microgrids integration

Federated-learning-based active fault management(AFM)is devised to achieve real-time safety assurance for microgrids and the main grid during faults.AFM was originally formulated as a distributed optimization problem.Here,federated learning is used to train each microgrid’s network with training data achieved from distributed optimization.The main contribution of this work is to replace the optimization-based AFM control algorithm with a learning-based AFM control algorithm.The replacement transfers computation from online to offline.With this replacement,the control algorithm can meet real-time requirements for a system with dozens of microgrids.By contrast,distributed-optimization-based fault management can output reference values fast enough for a system with several microgrids.More microgrids,however,lead to more computation time with optimization-based method.Distributed-optimization-based fault management would fail real-time requirements for a system with dozens of microgrids.Controller hardware-in-the-loop real-time simulations demonstrate that learning-based AFM can output reference values within 10 ms irrespective of the number of microgrids.

Applying real-time control to enhance the performance of nitrogen removal in CAST system

A bench-scale reactor（72 L） red with domestic sewage, was operated more than 3 months with three operation modes： traditional mode, modified mode and real-time control mode, so as to evaluate effects of the operation mode on the system performance and to develop a feasible control strategy. Results obtained from fixed-time control study indicate that the variations of the pH and oxidation-reduction potential（ORP） profiles can represent dynamic characteristics of system and the cycle sequences can be controlled and optimized by the control points on the pH and ORP profiles. A control strategy was, therefore, developed and applied to real-time control mode. Compared with traditional mode, the total nitrogen（TN） removal can be increased by approximately 16% in modified mode and a mean TN removal of 92% was achieved in real-time control mode. Moreover, approximately 12.5% aeration energy was saved in real- time control mode. The result of this study shows that the performance of nitrogen removal was enhanced in modified operation mode. Moreover, the real-time control made it possible to optimize process operation and save aeration energy.

Canadian children’s and youth’s adherence to the 24-h movement guidelines during the COVID-19 pandemic: A decision tree analysis

Purpose:The purpose of this study was to use decision tree modeling to generate profiles of children and youth who were more and less likely to meet the Canadian 24-h movement guidelines during the coronavirus disease-2019(COVID-19)outbreak.Methods:Data for this study were from a nationally representative sample of 1472 Canadian parents(Meanage=45.12,SD=7.55)of children(511 years old)or youth(1217 years old).Data were collected in April 2020 via an online survey.Survey items assessed demographic,behavioral,social,micro-environmental,and macro-environmental characteristics.Four decision trees of adherence and non-adherence to all movement recommendations combined and each individual movement recommendation(physical activity(PA),screen time,and sleep)were generated.Results:Results revealed specific combinations of adherence and non-adherence characteristics.Characteristics associated with adherence to the recommendation(s)included high parental perceived capability to restrict screen time,annual household income ofCAD 100,000,increases in children’s and youth’s outdoor PA/sport since the COVID-19 outbreak began,being a boy,having parents younger than 43 years old,and small increases in children’s and youth’s sleep duration since the COVID-19 outbreak began.Characteristics associated with non-adherence to the recommendation(s)included low parental perceived capability to restrict screen time,youth aged 1217 years,decreases in children’s and youth’s outdoor PA/sport since the COVID-19 outbreak began,primary residences located in all provinces except Quebec,low parental perceived capability to support children’s and youth’s sleep and PA,and annual household income ofCAD 99,999.Conclusion:Our results show that specific characteristics interact to contribute to(non)adherence to the movement behavior recommendations.Results highlight the importance of targeting parents’perceived capability for the promotion of children’s and youth’s movement behaviors during challenging times of the COVID-19 pandemic,paying particular attention to enhancing parental perceived capability to restrict screen time.

Efficient sampling for decision making in materials discovery

Accelerating materials discovery crucially relies on strategies that efficiently sample the search space to label a pool of unlabeled data.This is important if the available labeled data sets are relatively small compared to the unlabeled data pool.Active learning with efficient sampling methods provides the means to guide the decision making to minimize the number of experiments or iterations required to find targeted properties.We review here different sampling strategies and show how they are utilized within an active learning loop in materials science.

High-speed corner detection based on fuzzy ID3 decision tree

A high-speed comer detection algorithm based on fuzzy ID3 decision tree was proposed. In the algorithm, the Bresenham circle with 3-pixel radius was used as the test mask, overlapping the candidate comers with the nucleus. Connected pixels on the circle were applied to compare the intensity value with the nucleus, with the membership function used to give the fuzzy result. The pixel with maximum information gain was chosen as the parent node to build a binary decision tree. Thus, the comer detector was derived. The pictures taken in Fengtai Railway Station in Beijing were used to test the method. The experimental results show that when the number of pixels on the test mask is chosen to be 9, best result can be obtained. The comer detector significantly outperforms existing detector in computational efficiency without sacrificing the quality and the method also provides high performance against Poisson noise and Gaussian blur.

Simulation research of discrete sliding mode control for active power filter

Because of the widely-used nonlinear loads, the problems of harmonics and low power factor in power systems are becoming more and more serious. In view of the above problems, a shunt three-phase active power filter （SAPF） based on discrete sliding mode control to suppress the harmonics was designed and the power factor improved. First, built the mathematical model of SAPF. Then, controlled the switch through analyzing the harmonic current that was controlled signal using discrete sliding mode control. Through simulation using MATLAB, verified the validity of the algorithm. By the simulation waveforms, it can be found that after the load current containing a large number of harmonics passes the active power filter, the waveform of the power current approximately becomes a sine wave and the harmonics is significantly reduced. As a result, it plays a good role in purifying power systems. Moreover, from the waveforms of harmonic current and power current, it can be found that the algorithm has a faster tracking speed. The waveform can fect.

Neural mechanism of proposer's decision-making in the ultimatum and dictator games

Previous studies have demonstrated that reactions to unfair offers in the ultimatum game are correlated with negative emotion. However, little is known about the difference in neural activity between a proposer＇s decision-making in the ultimatum game compared with the dictator game. The present functional magnetic resonance imaging study revealed that proposing fair offers in the dictator game elicited greater activation in the right supramarginal gyrus, right medial frontal gyrus and left anterior cingulate cortex compared with proposing fair offers in the ultimatum game in 23 Chinese undergraduate and graduate students from Beijing Normal University in China. However, greater activation was found in the right superior temporal gyrus and left cingulate gyrus for the reverse contrast. ＂The results indicate that proposing fair offers in the dictator game is more strongly associated with cognitive control and conflicting information processing compared with proposing fair offers in the ultimatum game.

Real-time Operation Optimization in Active Distribution Networks Based on Multi-agent Deep Reinforcement Learning

The increasing integration of intermittent renewable energy sources(RESs)poses great challenges to active distribution networks(ADNs),such as frequent voltage fluctuations.This paper proposes a novel ADN strategy based on multiagent deep reinforcement learning(MADRL),which harnesses the regulating function of switch state transitions for the realtime voltage regulation and loss minimization.After deploying the calculated optimal switch topologies,the distribution network operator will dynamically adjust the distributed energy resources(DERs)to enhance the operation performance of ADNs based on the policies trained by the MADRL algorithm.Owing to the model-free characteristics and the generalization of deep reinforcement learning,the proposed strategy can still achieve optimization objectives even when applied to similar but unseen environments.Additionally,integrating parameter sharing(PS)and prioritized experience replay(PER)mechanisms substantially improves the strategic performance and scalability.This framework has been tested on modified IEEE 33-bus,IEEE 118-bus,and three-phase unbalanced 123-bus systems.The results demonstrate the significant real-time regulation capabilities of the proposed strategy.

基于Activiti和Drools的水产养殖自动决策流程管理系统

针对目前水产养殖过程管理中缺乏有效的流程化管理、养殖业务规则不明确、养殖决策效率低、人工经验判断操作失误率高等问题,阐述了工作流技术和规则引擎技术结合应用于水产养殖流程管理的设计思想。首先提出了一种基于规则引擎的智能工作流管理系统体系结构,并对系统进行总体框架设计。然后在分析和总结出水产养殖业务流程步骤繁琐不明确、受时间限制、多循环、多并发和存在大量养殖业务决策等特点的基础上,以南美白对虾养殖流程为例,通过Activiti可视化流程设计器对南美白对虾养殖流程进行流程定义和设计,构建水产养殖工作流模型;通过Drools规则引擎制定南美白对虾养殖关键流程业务规则库,制定过程包括养殖规则的分析、定义、设计、编写和触发。最后,将Activiti工作流引擎和Drools规则引擎与当今主流的SSH框架进行整合,开发基于Activiti和Drools的水产养殖自动决策流程管理系统。通过初期试验运行表明,该系统能有效实现水产养殖全流程业务状态的实时监控和养殖关键流程的规则决策,能有效增加养殖产量14.8%,降低饵料系数11.4%,减少人工管理成本30%,使得整体经济效益增加29.3%,初期试验效果良好,为水产养殖信息化过程管理提供了一种切实可行的流程化、自动化、精细化养殖的新策略。

Antiviral Activity of Recombinant Cyanovirin-N against HSV-1

In this study,a standard strain of HSV-1 (strain SM44) was used to investigate the antiviral activity of the recombinant Cyanovirin-N (CV-N) against Herpes simplex virus type 1 (HSV-1) in vitro and in vivo.Cytopathic effect (CPE) and MTT assays were used to evaluate the effect of CV-N on HSV-1 in Vero cells.The number of copies of HSV-DNA was detected by real-time fluorescence quantitative PCR (FQ-PCR).The results showed that CV-N had a low cytotoxicity on Vero cells with a CC50 of 359.03±0.56 μg/mL,and that it could not directly inactivate HSV-1 infectivity.CV-N not only reduced the CPE of HSV-1 when added before or after viral infection,with a 50% inhibitory concentration (IC50) with 2.26 and 30.16μg/mL respectively,but it also decreased the copies of HSV-1 DNA in infected host cells.The encephalitis model for HSV-1 infection was conducted in Kunming mice,and treated with three dosages of CV-N (0.5,5 & 10 mg/kg) which was administered intraperitoneally at 2h,3d,5d,7d post infection.The duration for the appearance of symptoms of encephalitis and the survival days were recorded and brain tissue samples were obtained for pathological examination (HE staining).Compared with the untreated control group,in the 5mg/kg CV-N and 10mg/kg CV-N treated groups,the mice suffered light symptoms and the number of survival days were more than 9d and 14d respectively.HE staining also showed that in 5mg/kg CV-N and 10mg/kg CV-N treated groups,the brain cells did not show visible changes,except for a slight inflammation.Our results demonstrated that CV-N has pronounced antiviral activity against HSV-1 both in vitro and in vivo,and it would be a promising new candidate for anti-HSV therapeutics.