The impact of the Rural Minimum Living Standard Guarantee(Rural Dibao)Program on child nutrition outcomes

The Rural Minimum Living Standard Guarantee(Rural Dibao)is an important unconditional cash transfer program to alleviate poverty in rural China.Despite the importance of children’s nutrition in breaking poverty cycles,little is known about the impact of Rural Dibao on child nutrition outcomes.Using China Family Panel Studies(CFPS),this paper examines the effects of Rural Dibao on child nutrition outcomes and investigates potential pathways and heterogeneous effects.We exploit propensity score matching and difference-in-differences techniques to evaluate the effects of the Rural Dibao program on child nutrition outcomes.Our results suggest that Rural Dibao significantly impacts the nutrition outcomes of children up to 15 years of age.Specifically,our results suggest that Rural Dibao improves child height-to-age z-scores by 1.05 standard deviations and lowers the probability of stunting by 11.9 percentage points.Additional analyses suggest that increased protein intake is the main pathway through which Rural Dibao participation contributes to better nutrition outcomes.We also find that the effect of the program is more pronounced among girls,children who are non-left-behind or live with highly educated mothers,and those from low-income families and poor areas.Our findings suggest that Rural Dibao participation helps improve child nutrition outcomes through improving diet quality.

Toward Trustworthy Decision-Making for Autonomous Vehicles:A Robust Reinforcement Learning Approach with Safety Guarantees

While autonomous vehicles are vital components of intelligent transportation systems,ensuring the trustworthiness of decision-making remains a substantial challenge in realizing autonomous driving.Therefore,we present a novel robust reinforcement learning approach with safety guarantees to attain trustworthy decision-making for autonomous vehicles.The proposed technique ensures decision trustworthiness in terms of policy robustness and collision safety.Specifically,an adversary model is learned online to simulate the worst-case uncertainty by approximating the optimal adversarial perturbations on the observed states and environmental dynamics.In addition,an adversarial robust actor-critic algorithm is developed to enable the agent to learn robust policies against perturbations in observations and dynamics.Moreover,we devise a safety mask to guarantee the collision safety of the autonomous driving agent during both the training and testing processes using an interpretable knowledge model known as the Responsibility-Sensitive Safety Model.Finally,the proposed approach is evaluated through both simulations and experiments.These results indicate that the autonomous driving agent can make trustworthy decisions and drastically reduce the number of collisions through robust safety policies.

Joint computation offloading and parallel scheduling to maximize delay-guarantee in cooperative MEC systems

The growing development of the Internet of Things(IoT)is accelerating the emergence and growth of new IoT services and applications,which will result in massive amounts of data being generated,transmitted and pro-cessed in wireless communication networks.Mobile Edge Computing(MEC)is a desired paradigm to timely process the data from IoT for value maximization.In MEC,a number of computing-capable devices are deployed at the network edge near data sources to support edge computing,such that the long network transmission delay in cloud computing paradigm could be avoided.Since an edge device might not always have sufficient resources to process the massive amount of data,computation offloading is significantly important considering the coop-eration among edge devices.However,the dynamic traffic characteristics and heterogeneous computing capa-bilities of edge devices challenge the offloading.In addition,different scheduling schemes might provide different computation delays to the offloaded tasks.Thus,offloading in mobile nodes and scheduling in the MEC server are coupled to determine service delay.This paper seeks to guarantee low delay for computation intensive applica-tions by jointly optimizing the offloading and scheduling in such an MEC system.We propose a Delay-Greedy Computation Offloading(DGCO)algorithm to make offloading decisions for new tasks in distributed computing-enabled mobile devices.A Reinforcement Learning-based Parallel Scheduling(RLPS)algorithm is further designed to schedule offloaded tasks in the multi-core MEC server.With an offloading delay broadcast mechanism,the DGCO and RLPS cooperate to achieve the goal of delay-guarantee-ratio maximization.Finally,the simulation results show that our proposal can bound the end-to-end delay of various tasks.Even under slightly heavy task load,the delay-guarantee-ratio given by DGCO-RLPS can still approximate 95%,while that given by benchmarked algorithms is reduced to intolerable value.The simulation results are demonstrated the effective-ness of DGCO-RLPS for delay guarantee in MEC.

Guarantee Strategy for the Safety of Agricultural Industry in Hunan Province

The safety of agricultural industry in Hunan Province shows an upward trend from"basically safe"to"very safe",but the state in the"safe"or"very safe"range is still unstable.In view of this,Hunan Province should guarantee the agricultural production ability,cultivate and enhance the core competitiveness of agriculture,firmly grasp the agricultural control power,attach importance to the export quality of agri-cultural products and other aspects to ensure the safety of agricultural industry.

Study on Urban Resilience Based on the Analysis of Supply Guarantee Facilities during Epidemic Closure—A Case Study of Shanghai in 2022

In the case of major public emergencies, the ability of cities to resist shocks becomes very important and reflects urban resilience. This paper selected the supply guarantee facilities during the city-wide lockdown of Shanghai during March-May 2022 due to COVID-19 pandemic as the research object. In this research, the per capita supply guarantee capacity and supply guarantee overlay intensity were analyzed based on the official list of facilities, and the actual role of the supply guarantee facilities was investigated through a public research questionnaire. The thermodynamic diagram map that was generated based on phone visits reflected the actual distribution of the population. Then the level of “supply guarantee resilience” was evaluated and graded for each district of Shanghai. It was concluded that the overall level of supply guarantee resilience was high in the central city, divergence in the near suburban districts, and generally low in the remote suburban districts. Based on this, the paper summarized the problems of supply guarantee revealed in Shanghai during the epidemic lockdown as well as proposed strategies to improve the resilience of similar scenarios in the future. With the help of big data and public research tools, this paper aimed to provide ways and methods to evaluate the resilience of cities under major public emergencies.

基于Assume-Guarantee搜索复用的C程序验证方法

提出了一种基于Assume-Guarantee搜索复用的验证方法,对C程序源代码进行验证.其思想是,在程序的每点处都引入一个保守假设条件,并假设从任意点出发,变量取值满足该点假设条件的所有执行路径都不会违背给定性质,然后根据这些假设条件遍历所有可能的执行路径以验证给定的时序安全性质,并在遍历的过程中验证这些假设条件是否满足,如果不满足,则不断对其精化和加强.验证方法总是在保证假设条件可靠的前提下尽量使用较弱的条件,使得大量的执行路径由于满足假设条件而可以搜索复用,从而降低验证代价.应用该方法验证了Linux操作系统中SSL协议的实现程序openssl-0.9.6c满足SSL协议的初始握手规范.实验结果表明,该方法具有良好的实用性和可扩展性.

Research on Guaranteed Scheduling Algorithms

Guaranteed scheduling is necessary for hard real time systems, because each process of them must meet their deadline, or a serious consequence will result.In this paper we discuss two guaranteed schedule algorithms:backtracking and branch and bound,introduce the process to find the optimal solution by both methods,propose the concept of logical node and physical node.Through some experiments for different process sets,we have made comparisons between the two algorithms in branch nodes,comparing time,topology of the search tree,memory size needed,etc.

Establishment of Safety Guarantee System of Mountainous Tourism——A Case Study of High and Higher Mountains

After summarizing researches on domestic and foreign tourism safety,it was found that there were few research results on mountainous tourism safety,especially tourism safety and tourism safety guarantee system of high and higher mountains with high risk.The paper had concluded hidden dangers and sources of safe accidents of mountainous tourism,and studied tourism safety guarantee system of high and higher mountains.Furthermore,it proposed that tourism safety guarantee system was composed of tourism safety policies and regulations,tourism precaution,tourism safety control,tourism safety rescue and tourism insurance;and finally pointed out components of each factor.

The Present Situation of Chattel Guarantee System and Its Improvements—Taking the Angle of American Uniform Commercial Code(UCC)

Although there are appropriate stipulations for the chattel guarantees in the law of China, this guarantee system could not adapt to the request of economy's development because of the following reasons: the scope of chattel guarantees is narrow according to relevant stipulations; the transaction cost of the chattel is high; mortgage registration of chattel is in a mess; lack of efficiently executive guarantee system, etc. To counter the problems existing in the present Chinese chattel guarantee system, in this article, the author proposed some corresponding suggestions and countermeasures, hoping to perfect the chattel guarantee system in China.

Providing Guaranteed Network Performance across Tenants:Advances,Challenges and Opportunities

The varied network performance in the cloud hurts application performance.This increases the tenant’s cost and becomes the key hindrance to cloud adoption.It is because virtual machines(VMs)belonging to one tenant can reside in multiple physical servers and communication interference across tenants occasionally occurs when encountering network congestion.In order to prevent such unpredictability,it is critical for cloud providers to offer the guaranteed network performance at tenant level.Such a critical issue has drawn increasing attention in both academia and industry.Many elaborate mechanisms are proposed to provide guaranteed network performance,such as guaranteed bandwidth or bounded message delay across tenants.However,due to the intrinsic complexities and limited capabilities of commodity hardware,the deployment of these mechanisms still faces great challenges in current cloud datacenters.Moreover,with the rapid development of new technologies,there are new opportunities to improve the performance of existing works,but these possibilities are not under full discussion yet.Therefore,in this paper,we survey the latest development of the network performance guarantee approaches and summarize them based on their features.Then,we explore and discuss the possibilities of using emerging technologies as knobs to upgrade the performance or overcome the inherent shortcomings of existing advances.We hope this article will help readers quickly Received:Apr.07,2020 Revised:Oct.23,2020 Editor:Haifeng Zheng understand the causes of the problems and serve as a guide to motivate researchers to develop innovative algorithms and frameworks.

Improving China's Legal System for Product Quality Guarantees ——A legal analysi s of product quality guarantee regulation by the Government

It is the responsibility of governments to supervise and regulateproduct quality to protect consumers and prevent failures in the product qualityguarantee system.Appropriate supervision will help safeguard the interests ofconsumers,promote product quality,and resolve disputes.The extent of supervisionshould be guided by the principle of need for state intervention andneeds to be highly diversified.

The eco-environmental guarantee for China's urbanization process

Studying the change of resources consumption and eco-environmental carrying capacity are of importance to the sustainable development of urbanization.Based on the China's economic and social statistical data from 1950 to 2006,the ecological footprint,eco-logical footprint intensity,ecological deficit and surplus,and eco-environment quality com-prehensive index are calculated,the correlation between urbanization and eco-environmental change is analyzed and the eco-environmental guarantee for China's urbanization in 2030 is forecasted.The major results could be summarized as follows:(1) there is a positive linear relation between urbanization and ecological footprint,negative linear relation between ur-banization and ecological footprint intensity,ecological deficit and surplus and the negative exponential relation between urbanization and eco-environment quality comprehensive index.(2) By 2030,the urbanization level will reach 61.32%,the ecological deficit will increase to 42.2866×108 hm2 and the eco-environment quality comprehensive index will drop to 0.3016 on the condition that the total quantity ecological footprint achieves 55.9348×108 hm2.(3) Under the existing urban development pattern,the ecological overload will be more serious in the next 24 years.Constructing the reasonable industrial structure and establishing the intensive resources utilization system to alleviate the eco-environmental pressure are the tough challenges in China's urbanization process.

An LMI Method to Robust Iterative Learning Fault-tolerant Guaranteed Cost Control for Batch Processes

Based on an equivalent two-dimensional Fornasini-Marchsini model for a batch process in industry, a closed-loop robust iterative learning fault-tolerant guaranteed cost control scheme is proposed for batch processes with actuator failures. This paper introduces relevant concepts of the fault-tolerant guaranteed cost control and formulates the robust iterative learning reliable guaranteed cost controller (ILRGCC). A significant advantage is that the proposed ILRGCC design method can be used for on-line optimization against batch-to-batch process uncertainties to realize robust tracking of set-point trajectory in time and batch-to-batch sequences. For the convenience of implementation, only measured output errors of current and previous cycles are used to design a synthetic controller for iterative learning control, consisting of dynamic output feedback plus feed-forward control. The proposed controller can not only guarantee the closed-loop convergency along time and cycle sequences but also satisfy the H∞performance level and a cost function with upper bounds for all admissible uncertainties and any actuator failures. Sufficient conditions for the controller solution are derived in terms of linear matrix inequalities (LMIs), and design procedures, which formulate a convex optimization problem with LMI constraints, are presented. An example of injection molding is given to illustrate the effectiveness and advantages of the ILRGCC design approach.

Decentralized robust guaranteed cost control for a class of interconnected singular large-scale systems with time-delay and parameter uncertainty

The decentralized robust guaranteed cost control problem is studied for a class of interconnected singular large-scale systems with time-delay and norm-bounded time-invariant parameter uncertainty under a given quadratic cost performance function. The problem that is addressed in this study is to design a decentralized robust guaranteed cost state feedback controller such that the closed-loop system is not only regular, impulse-free and stable, but also guarantees an adequate level of performance for all admissible uncertainties. A sufficient condition for the existence of the decentralized robust guaranteed cost state feedback controllers is proposed in terms of a linear matrix inequality （LMI） via LMI approach. When this condition is feasible, the desired state feedback decentralized robust guaranteed cost controller gain matrices can be obtained. Finally, an illustrative example is provided to demonstrate the effectiveness of the proposed approach.

Guaranteed Cost Consensus for High-dimensional Multi-agent Systems With Time-varying Delays

Guaranteed cost consensus analysis and design problems for high-dimensional multi-agent systems with time varying delays are investigated. The idea of guaranteed cost con trol is introduced into consensus problems for high-dimensiona multi-agent systems with time-varying delays, where a cos function is defined based on state errors among neighboring agents and control inputs of all the agents. By the state space decomposition approach and the linear matrix inequality(LMI)sufficient conditions for guaranteed cost consensus and consensu alization are given. Moreover, a guaranteed cost upper bound o the cost function is determined. It should be mentioned that these LMI criteria are dependent on the change rate of time delays and the maximum time delay, the guaranteed cost upper bound is only dependent on the maximum time delay but independen of the Laplacian matrix. Finally, numerical simulations are given to demonstrate theoretical results.

Delay-independent robust guaranteed-cost control for uncertain linear neutral systems

This article concerns the delay-independent guaranteed-cost control problem via memoryless state feedback for a class of neutral-type systems with structural uncertainty and a given quadratic cost function. New delay-independent conditions for the existence of the guaranteed-cost controller are presented in the term of LMIs. An algorithm involving optimization is proposed to design a controller achieving an optimal guaranteed-cost, such that, the system can be stabilized for all admissible uncertainties. A numerical example is provided to illustrate the feasibility of the proposed method.

Robust reliable guaranteed cost control for uncertain singular systems with time-delay

The robust reliable guaranteed cost control for uncertain singular delay systems with actuator failures and a given quadratic cost function is studied. The system under consideration involves constant time-delay and norm-bounded parameter uncertainties. The purpose is to design state feedback controllers which can tolerate actuator failure, such that the closed-loop system is stable, and the specified cost function has an upper bound for all admissible uncertainties. The sufficient conditions for the solvability of this problem are obtained by a linear matrix inequality （LMI） method. Furthermore, a numerical example is given to demonstrate the applicability of the proposed approach.

Non-fragile guaranteed cost control of discrete-time fuzzy bilinear system

This paper focuses on the problem of non-fragile guaranteed cost control for a class of T-S discrete-time fuzzy bilinear systems（DFBS）.Based on the parallel distributed compensation（PDC） approach,the sufficient conditions are derived such that the closed-loop system is asymptotically stable and the cost function value is no more than a certain upper bound in the presence of the additive controller gain perturbations.The non-fragile guaranteed cost controller can be obtained by solving a set of bilinear matrix inequalities（BMIs）.The Van de Vusse model is utilized to demonstrate the validity and effectiveness of the proposed approach.

Guaranteed Cost Active Fault-tolerant Control of Networked Control System with Packet Dropout and Transmission Delay

The problem of guaranteed cost active fault-tolerant controller （AFTC） design for networked control systems （NCSs） with both packet dropout and transmission delay is studied in this paper. Considering the packet dropout and transmission delay, a piecewise constant controller is adopted. With a guaranteed cost function, optimal controllers whose number is equal to the number of actuators are designed, and the design process is formulated as a convex optimal problem that can be solved by existing software. The control strategy is proposed as follows： when actuator failures appear, the fault detection and isolation unit sends out the information to the controller choosing strategy, and then the optimal stabilizing controller with the smallest guaranteed cost value is chosen. Two illustrative examples are given to demonstrate the effectiveness of the proposed approach. By comparing with the existing methods, it can be seen that our method has a better performance.

Guaranteed cost control of networked control systems under limited communication capacity and variable sampling

The problem of guaranteed cost control for the networked control systems(NCSs) with time-varying delays, time-varying sampling intervals and signals quantization was investigated, wherein the physical plant was continuous-time one, and the control input was discrete-time one. By using an input delay approach and a sector bound method, the network induced delays, quantization parameter and sampling intervals were presented in one framework in the case of the state and the control input by quantized in a logarithmic form. A novel Lyapunov function with discontinuity, which took full advantages of the NCS characteristic information, was exploited. In addition, it was shown that Lyapunov function decreased at the jump instants. Furthermore, the Leibniz-Newton formula and free-weighting matrix methods were used to obtain the guaranteed cost controller design conditions which were dependent on the NCS characteristic information. A numerical example was used to illustrate the effectiveness of the proposed methods.