Effect of Jianpi Shengxue Tablet on Iron Metabolism and Nutritional Status in Patients with Renal Anemia:A Prospective,Randomized,Open,Parallel Controlled and Multicenter Clinical Study

Objective This study aimed to analyze the clinical efficacy of the Jianpi Shengxue tablet for treating renal anemia.Methods A total of 200 patients with renal anemia from December 2020 to December 2022 were enrolled and randomly divided into two groups.Patients in the control group were treated with polysaccharide-iron complex,and those in the experimental group were administered Jianpi Shengxue tablet.After 8 weeks of continuous treatment,the therapeutic outcomes regarding anemia were compared between the two groups.Results After treatment,the red blood cell(RBC)count,hematocrit(HCT),reticulocyte percentage(RET),ferritin(SF),serum iron(SI),transferrin saturation(TSAT),and serum albumin(ALB)all increased(P<0.01),and the clinical symptom score and total iron binding capacity decreased(P<0.01)in the experimental group.Moreover,the improvements in RBC,HCT,RET,SF,SI,TAST,ALB,and clinical symptoms(fatigue,anorexia,dull skin complexion,numbness of hands and feet)in the experimental group were significantly greater than those in the control group(P<0.05).The total effective rate for treating renal anemia was significantly higher in the experimental group than in the control group(P<0.01).Conclusion The Jianpi Shengxue tablet demonstrates efficacy in treating renal anemia,leading to significant improvements in the laboratory examination results and clinical symptoms of patients with renal anemia.

Parallel Neural Network-Based Motion Controller for Autonomous Underwater Vehicles

A parallel neural network-based controller （PNNC） is presented for the motion control of underwater vehicles in this paper. It consists of a real-time part, a self-learning part and a desired-state programmer, and it is different from normal adaptive neural network controller in structure. Owing to the introduction of the self-learning part, on-line learning can be performed without sample data in several sample periods, resulting in high learning speed of the controller and good control performance. The desired-state programmer is utilized to obtain better learning samples of the neural network to keep the stability of the controller. The developed controller is applied to the 4-degree of freedom control of the AUV “IUV- IV” and is successful on the simulation platform. The control performance is also compared with that of neural network controller with different structures such as normal adaptive neural network and different learning methods. Current effects and surge velocity control are also included to demonstrate the controller＇ s performance. It is shown that the PNNC has a great possibility to solve the problems in the control system design of underwater vehicles.

Parallel Control for Optimal Tracking via Adaptive Dynamic Programming

This paper studies the problem of optimal parallel tracking control for continuous-time general nonlinear systems.Unlike existing optimal state feedback control,the control input of the optimal parallel control is introduced into the feedback system.However,due to the introduction of control input into the feedback system,the optimal state feedback control methods can not be applied directly.To address this problem,an augmented system and an augmented performance index function are proposed firstly.Thus,the general nonlinear system is transformed into an affine nonlinear system.The difference between the optimal parallel control and the optimal state feedback control is analyzed theoretically.It is proven that the optimal parallel control with the augmented performance index function can be seen as the suboptimal state feedback control with the traditional performance index function.Moreover,an adaptive dynamic programming(ADP)technique is utilized to implement the optimal parallel tracking control using a critic neural network(NN)to approximate the value function online.The stability analysis of the closed-loop system is performed using the Lyapunov theory,and the tracking error and NN weights errors are uniformly ultimately bounded(UUB).Also,the optimal parallel controller guarantees the continuity of the control input under the circumstance that there are finite jump discontinuities in the reference signals.Finally,the effectiveness of the developed optimal parallel control method is verified in two cases.

Parallel Control for Continuous-Time Linear Systems:A Case Study

In this paper,a new parallel controller is developed for continuous-time linear systems.The main contribution of the method is to establish a new parallel control law,where both state and control are considered as the input.The structure of the parallel control is provided,and the relationship between the parallel control and traditional feedback controls is presented.Considering the situations that the systems are controllable and incompletely controllable,the properties of the parallel control law are analyzed.The parallel controller design algorithms are given under the conditions that the systems are controllable and incompletely controllable.Finally,numerical simulations are carried out to demonstrate the effectiveness and applicability of the present method.Index Terms-Continuous-time linear systems,digital twin,parallel controller,parallel intelligence,parallel systems.

The DAO to MetaControl for MetaSystems in Metaverses:The System of Parallel Control Systems for Knowledge Automation and Control Intelligence in CPSS

An investigation and outline of MetaControl and DeControl in Metaverses for control intelligence and knowledge automation are presented.Prescriptive control with prescriptive knowledge and parallel philosophy is proposed as the starting point for the new control philosophy and technology,especially for computational control of metasystems in cyberphysical-social systems.We argue that circular causality,the generalized feedback mechanism for complex and purposive systems,should be adapted as the fundamental principle for control and management of metasystems with metacomplexity in metaverses.Particularly,an interdisciplinary approach is suggested for MetaControl and DeControl as a new form of intelligent control based on five control metaverses:MetaVerses,MultiVerses,InterVerses,TransVerse,and DeepVerses.

DeCASA in AgriVerse: Parallel Agriculture for Smart Villages in Metaverses

The demand for food is tremendously increasing with the growth of the world population,which necessitates the development of sustainable agriculture under the impact of various factors,such as climate change.To fulfill this challenge,we are developing Metaverses for agriculture,referred to as Agri Verse,under our Decentralized Complex Adaptive Systems in Agriculture(De CASA)project,which is a digital world of smart villages created alongside the development of Decentralized Sciences(De Sci)and Decentralized Autonomous Organizations(DAO)for Cyber-Physical-Social Systems(CPSSs).Additionally,we provide the architectures,operating modes and major applications of De CASA in AgriVerse.For achieving sustainable agriculture,a foundation model based on ACP theory and federated intelligence is envisaged.Finally,we discuss the challenges and opportunities.

Research Progress of Parallel Control and Management

Based on ACP(artificial systems,computational experiments,and parallel execution)methodology,parallel control and management has become a popularly systematic and complete solution for the control and management of complex systems.This paper focuses on summarizing comprehensive review of the research literature of parallel control and management achieved in the recent years including the theoretical framework,core technologies,and the application demonstration.The future research,application directions,and suggestions are also discussed.

MODELING AND CONTROLLING OF PARALLEL MANIPULATOR JOINT DRIVEN BY PNEUMATIC MUSCLES

A parallel manipulator joint driven by three pneumatic muscles and its posture control strategy are presented. Based on geometric constraints and dynamics, a system model is developed through which some influences on dynamic response and open-loop gain are analyzed including the supply pressure, the initial pressure and the volume of pneumatic muscle. A sliding-mode controller with a nonlinear switching function is applied to control posture, which adopts the combination of a main method that separates control of each muscle and an auxiliary method that postures error evaluation of multiple muscles, especially adopting the segmented and intelligent adjustments of sliding-mode parameters to fit different expected postures and initial states. Experimental results show that this control strategy not only amounts to the steady-state error of 0. 1° without overshoot, but also achieves good trajectory tracking.

Robust scheme of global parallel force/position regulators for robot manipulators under environment uncertainty

A simple robust scheme of parallel force/position control is proposed in this paper to deal with two problems for non-planar constraint surface and nonlinear mechanical feature of environment： i） uncertainties in environment that are usually not available or difficult to be determined in most practical situations; ii） stability problem or/and integrator windup due to the integration of force error in the force dominance rule in parallel force/position control. It shows that this robust scheme is a good alternative for anti-windup. In the presence of environment uncertainties, global asymptotic stability of the resulting closed-loop system is guaranteed; it environment with complex characteristics. Finally, numerical robot manipulator. also shows robustness of the proposed controller to uncertain simulation verifies results via contact task of a two rigid-links

Control 5.0: From Newton to Merton in Popper's Cyber-Social-Physical Spaces

The future of control in cyberspace of parallel worlds is discussed. It argues for the coming age of Control 5.0,the control technology for the new IT capable of dealing with artificial worlds with VR, AR, AI and robotics. The discipline of automation needs a new interpretation of its core knowledge and skill set of modeling, analysis, and control for cyber-socialphysical systems, and a paradigm shift from Newtonian Systems with Newton's Laws or Big Laws with Small Data to Mertonian Systems with Merton's Laws or Small Laws with Big Data.

Temperature Control System with Multi-closed Loops for Lithography Projection Lens

Image quality is one of the most important specifications of optical lithography tool and is affected notably by temperature, vibration, and contamination of projection lens（PL）. Traditional method of local temperature control is easier to introduce vibration and contamination, so temperature control system with multi-closed loops is developed to control the temperature inside the PL, and to isolate the influence of vibration and contamination. A new remote indirect-temperature-control（RITC） method is proposed in which cooling water is circulated to perform indirect-temperature-control of the PL. Heater and cooler embedded temperature control unit（TCU） is used to condition the temperature of the cooling water, and the TCU must be kept away from the PL so that the influence of vibration and contamination can be avoided. A new multi-closed loops control structure incorporating an internal cascade control structure（CCS） and an external parallel cascade control structure（PCCS） is designed to prevent large inertia, multi-delay, and multi-disturbance of the RITC system. A nonlinear proportional-integral（PI） algorithm is applied to further enhance the convergence rate and precision of the control process. Contrast experiments of different control loops and algorithms were implemented to verify the impact on the control performance. It is shown that the temperature control system with multi-closed loops reaches a precision specification at ±0.006 ℃ with fast convergence rate, strong robustness, and self-adaptability. This method has been successfully used in an optical lithography tool which produces a pattern of 100 nm critical dimension（CD）, and its performances are satisfactory.

Social Energy:Mining Energy From the Society

The inherent nature of energy,i.e.,physicality,sociality and informatization,implies the inevitable and intensive interaction between energy systems and social systems.From this perspective,we define "social energy" as a complex sociotechnical system of energy systems,social systems and the derived artificial virtual systems which characterize the intense intersystem and intra-system interactions.The recent advancement in intelligent technology,including artificial intelligence and machine learning technologies,sensing and communication in Internet of Things technologies,and massive high performance computing and extreme-scale data analytics technologies,enables the possibility of substantial advancement in socio-technical system optimization,scheduling,control and management.In this paper,we provide a discussion on the nature of energy,and then propose the concept and intention of social energy systems for electrical power.A general methodology of establishing and investigating social energy is proposed,which is based on the ACP approach,i.e., "artificial systems"(A), "computational experiments"(C) and "parallel execution"(P),and parallel system methodology.A case study on the University of Denver(DU) campus grid is provided and studied to demonstrate the social energy concept.In the concluding remarks,we discuss the technical pathway,in both social and nature sciences,to social energy,and our vision on its future.

Fuzzy energy management strategy for parallel HEV based on pigeon-inspired optimization algorithm

Improvements in fuel consumption and emissions of hybrid electric vehicle(HEV)heavily depend upon an efficient energy management strategy(EMS).This paper presents an optimizing fuzzy control strategy of parallel hybrid electric vehicle em-

A dual control strategy for power sharing improvement in islanded mode of AC microgrid

Parallel operation of inverter modules is the solution to increase the reliability,efficiency,and redundancy of inverters in microgrids.Load sharing among inverters in distributed generators(DGs)is a key issue.This study investigates the feasibility of power-sharing among parallel DGs using a dual control strategy in islanded mode of a microgrid.PQ control and droop control techniques are established to control the microgrid operation.P-f and Q-E droop control is used to attain real and reactive power sharing.The frequency variation caused by load change is an issue in droop control strategy whereas the tracking error of inverter power in PQ control is also a challenge.To address these issues,two DGs are interfaced with two parallel inverters in an islanded AC microgrid.PQ control is investigated for controlling the output real and reactive power of the DGs by assigning their references.The inverter under enhanced droop control implements power reallocation to restore the frequency among the distributed generators with predefined droop characteristics.A dual control strategy is proposed for the AC microgrid under islanded operation without communication link.Simulation studies are carried out using MATLAB/SIMULINK and the results show the validity and effective power-sharing performance of the system while maintaining a stable operation when the microgrid is in islanding mode.

Orthogonality of Redesigned tRNA Molecules with Three Stop Codons

The ability to expand genetic code in living cells has emerged as a powerful method with diverse applications.Here,we design re-placement of the anticodons of E.coli tRNAs that recognize codons for 20 natural amino acids,with three anti-stop codons,resulting in a total of 60 engineered tRNA constructs.We test these constructs one by one in E.coli,and found that six tRNAsCUA(tyrV,serX,hisR,trpT,glnV and leuX),two tRNAsUCA(trpT and leuX)and one tRNAUUA(tyrV)allowed efficient expression of Red Fluorescence Protein(RFP)with the presence of a corresponding stop codon in frame.Furthermore,we exploit the mutual orthogonality of tRNASer CUA,tRNATrpUCA and tRNATyrUUA with corresponding stop codons and demonstrated that the tRNASer CUA and the tRNATrp UCA can provide dynamic range and low crosstalk.Finally,we show the TAG and TGA can not only be used as an"AND gate"circuit to control the translation of target gene,but also be used to control the translation of a prodeoxyviolacein(PDV)pathway and a reporter in parallel.Overall,this work provides flexible tools for translational control and holds great potential to promote synthetic biology studies.

New Time-varying Fuzzy Sets Based on a PSO Midpoint of the Universe of Discourse

The paper presents a robust parallel distributed compensation （PDC） fuzzy controller for a nonlinear and certain system in continuous time described by the Tal^gi-Sugeno （T-S） fuzzy model. This controller is based on a new type of time-varying fuzzy sets （TVFS）. These fuzzy sets are characterized by displacement of the kernels to the right or left of the universe of discourse, and they are directed by a well-defined criterion. In this work, we only focused on the movement of midpoint of the universe. The movements of this midpoint are optimized by particle swarm optimization （PSO） approach.