延安市子长县社区体育现状分析与对策

社区体育是社区文化的重要方面,它对于丰富社区居民的生活,提高居民的身体素质,促进社区发展和社会进步有着重要的意义和内涵。本文将子长县社区体育开展现状进行调查和研究,探讨社区体育发展存在的问题,结果显示封闭的地理环境制约了该县社区体育的发展,也禁锢着人们的思想意识,使得该县人们参加体育运动的意识冷漠。所以我县要抓住新农村建设的有利时机,借助外部力量依靠自身优势大为发展,社区体育基础设施建设,丰富社区体育文化。逐步提高人们参与体育运动的意识,从而促进我县社区体育全面发展。

Development Status and Research Prospect of Mustard Vegetables Industry

The present study set its research background in the scientific develop- ment at present and in the future, the actual production needs, and the goal of building a bigger and stronger mustard industry. On the basis of a comprehensive and systematic investigation and a scientific analysis of the development status of mustard industry, especially the technical bottlenecks and problems constraining the industrialized production of mustard in south China, the present study proposed spe- cific research ideas, prospects, suggestions and measures accordingly. It was hoped to provide powerful technical support to promote the industrialized, healthy and sus- tainable development of the mustard industry in south China, and be of practical im- plications for the enrichment of people＇s ＂vegetable baskets＂ and the restructuring of the vegetable industry.

Necessary and Sufficient Conditions for Consensus in Third Order Multi-Agent Systems

We deal with a consensus control problem for a group of third order agents which are networked by digraphs.Assuming that the control input of each agent is constructed based on weighted difference between its states and those of its neighbor agents, we aim to propose an algorithm on computing the weighting coefficients in the control input. The problem is reduced to designing Hurwitz polynomials with real or complex coefficients. We show that by using Hurwitz polynomials with complex coefficients, a necessary and sufficient condition can be obtained for designing the consensus algorithm. Since the condition is both necessary and sufficient, we provide a kind of parametrization for all the weighting coefficients achieving consensus. Moreover, the condition is a natural extension to second order consensus, and is reasonable and practical due to its comparatively decreased computation burden. The result is also extended to the case where communication delay exists in the control input.

Machine leaming for internet of things data analysis： a survey

Rapid developments in hardware, software, and communication technologies have facilitated the emergence of Internet-connected sensory devices that provide observations and data measurements from the physical world. By 2020, it is estimated that the total number of Internet-connected devices being used will be between 25 and 50 billion. As these numbers grow and technologies become more mature, the volume of data being published will increase. The technology of Internet-connected devices, referred to as Internet of Things （IoT）, continues to extend the current Internet by providing connectivity and interactions between the physical and cyber worlds. In addition to an increased volume, the IoT generates big data characterized by its velocity in terms of time and location dependency, with a variety of multiple modalities and varying data quality. Intelligent processing and analysis of this big data are the key to developing smart IoT applications. This article assesses the various machine learning methods that deal with the challenges presented by IoT data by considering smart cities as the main use case. The key contribution of this study is the presentation of a taxonomy of machine learning algorithms explaining how different techniques are applied to the data in order to extract higher level information. The potential and challenges of machine learning for IoT data analytics will also be discussed. A use case of applying a Support Vector Machine （SVM） to Aarhus smart city traffic data is presented for a more detailed exploration.

Adaptive Neural Network-Based Control for a Class of Nonlinear Pure-Feedback Systems With Time-Varying Full State Constraints

Abstract--In this paper, an adaptive neural network （NN） control approach is proposed for nonlinear pure-feedback sys- tems with time-varying full state constraints. The pure-feedback systems of this paper are assumed to possess nonlinear function uncertainties. By using the mean value theorem, pure-feedback systems can be transformed into strict feedback forms. For the newly generated systems, NNs are employed to approximate unknown items. Based on the adaptive control scheme and backstepping algorithm, an intelligent controller is designed. At the same time, time-varying Barrier Lyapunov functions （BLFs） with error variables are adopted to avoid violating full state constraints in every step of the backstepping design. All closed- loop signals are uniformly ultimately bounded and the output tracking error converges to the neighborhood of zero, which can be verified by using the Lyapunov stability theorem. Two simulation examples reveal the performance of the adaptive NN control approach. Index TermsmAdaptive control, neural networks （NNs）, non- linear pure-feedback systems, time-varying constraints.

Hazard-evaluation-oriented Moving Horizon Parallel Steering Control for Driver-Automation Collaboration During Automated Driving

Prompted by emerging developments in connected and automated vehicles, parallel steering control, one aspect of parallel driving, has become highly important for intelligent vehicles for easing the burden and ensuring the safety of human drivers. This paper presents a parallel steering control framework for an intelligent vehicle using moving horizon optimization.The framework considers lateral stability, collision avoidance and actuator saturation and describes them as constraints, which can blend the operation of a human driver and a parallel steering controller effectively. Moreover, the road hazard and the steering operation error are employed to evaluate the operational hazardous of an intelligent vehicle. Under the hazard evaluation,the intelligent vehicle will be mainly operated by the human driver when the vehicle operates in a safe and stable manner.The automated steering driving objective will play an active role and regulate the steering operations of the intelligent vehicle based on the hazard evaluation. To verify the effectiveness of the proposed hazard-evaluation-oriented moving horizon parallel steering control approach, various validations are conducted, and the results are compared with a parallel steering scheme that does not consider automated driving situations. The results illustrate that the proposed parallel steering controller achieves acceptable performance under both conventional conditions and hazardous conditions.

Predictive Tracking Control of Network-Based Agents With Communication Delays

This paper investigates the remote tracking control problem of Network-based Agents with communication delays existing in both forward and feedback communication channels.A networked predictive tracking controller is proposed to compensate the negative effects caused by bilateral time-delays in a wireless network. Furthermore, the problem of consecutive data loss in the feedback channel is solved using aforementioned controller, where lateral movement perturbations are introduced.Simulations and experiments are provided for several cases,which verify the realizability and effectiveness of the proposed controller.

A Filtering Approach Based on MMAE for a SINS/CNS Integrated Navigation System

This paper explores multiple model adaptive estimation(MMAE) method, and with it, proposes a novel filtering algorithm. The proposed algorithm is an improved Kalman filter— multiple model adaptive estimation unscented Kalman filter(MMAE-UKF) rather than conventional Kalman filter methods,like the extended Kalman filter(EKF) and the unscented Kalman filter(UKF). UKF is used as a subfilter to obtain the system state estimate in the MMAE method. Single model filter has poor adaptability with uncertain or unknown system parameters,which the improved filtering method can overcome. Meanwhile,this algorithm is used for integrated navigation system of strapdown inertial navigation system(SINS) and celestial navigation system(CNS) by a ballistic missile's motion. The simulation results indicate that the proposed filtering algorithm has better navigation precision, can achieve optimal estimation of system state, and can be more flexible at the cost of increased computational burden.

3D bioprinting： an emerging technology full of opportunities and challenges

Three-dimensional （3D） printing is a novel promising technology based on 3D imaging and layer-by-layer additive fabrication. It has a profound influence on all aspects of our lives and is playing an increasing important role in many areas including engineering, manufacturing, art, education and medicine. ＂3D bioprinting＂ has been put forward with the technical progress in 3D printing and might be a possible way to solve the serious problem of human organ shortage in tissue engineering and regenerative medicine. Many research groups flung them into this area and have already made some gratifying achievements. However, it is a long way to fabricate a live organ. Many elements lead to the limitation of 3D bioprinting. This review introduces the background and development history of 3D bioprinting, compares different approaches of 3D bioprinting and illustrates the key factors of the printing process. Meanwhile, this review also points out existing challenges of 3D bioprinting and has a great prospect. Some points proposed in this review might be served as reference for the research of this field.

Using the Fractional Order Method to Generalize Strengthening Buffer Operator and Weakening Buffer Operator

To reveal the relationship between a weakening buffer operator and strengthening buffer operator, the traditional integer order buffer operator is extended to one that is fractional order. Fractional order buffer operator not only can generalize the weakening buffer operator and the strengthening buffer operator, but also results in small adjustments of the buffer effect.The effectiveness of the grey model(GM(1,1)) with the fractional order buffer operator is validated by six cases.

A survey on rough set theory and its applications

After probability theory, fuzzy set theory and evidence theory, rough set theory is a new mathematical tool for dealing with vague, imprecise, inconsistent and uncertain knowledge. In recent years, the research and applications on rough set theory have attracted more and more researchers＇ attention. And it is one of the hot issues in the artificial intelligence field. In this paper, the basic concepts, operations and characteristics on the rough set theory are introduced firstly, and then the extensions of rough set model, the situation of their applications, some application software and the key problems in applied research for the rough set theory are presented.

The Cubic Trigonometric Automatic Interpolation Spline

A class of cubic trigonometric interpolation spline curves with two parameters is presented in this paper. The spline curves can automatically interpolate the given data points and become C^2 interpolation curves without solving equations system even if the interpolation conditions are fixed. Moreover, shape of the interpolation spline curves can be globally adjusted by the two parameters. By selecting proper values of the two parameters,the optimal interpolation spline curves can be obtained.

Predicting Resting-state Functional Connectivity With Efficient Structural Connectivity

The complex relationship between structural connectivity(SC) and functional connectivity(FC) of human brain networks is still a critical problem in neuroscience. In order to investigate the role of SC in shaping resting-state FC, numerous models have been proposed. Here, we use a simple dynamic model based on the susceptible-infected-susceptible(SIS) model along the shortest paths to predict FC from SC. Unlike the previous dynamic model based on SIS theory, we focus on the shortest paths as the principal routes to transmit signals rather than the empirical structural brain network. We first simplify the structurally connected network into an efficient propagation network according to the shortest paths and then combine SIS infection theory with the efficient network to simulate the dynamic process of human brain activity. Finally, we perform an extensive comparison study between the dynamic models embedded in the efficient network, the dynamic model embedded in the structurally connected network and dynamic mean field(DMF) model predicting FC from SC. Extensive experiments on two different resolution datasets indicate that i) the dynamic model simulated on the shortest paths can predict FC among both structurally connected and unconnected node pairs; ii) though there are fewer links in the efficient propagation network, the predictive power of FC derived from the efficient propagation network is better than the dynamic model simulated on a structural brain network; iii) in comparison with the DMF model,the dynamic model embedded in the shortest paths is found to perform better to predict FC.

ACP-based social computing and parallel intelligence： Societies 5.0 and beyond

Social computing, as the technical foundation of future computational smart societies, has the potential to improve the effectiveness of opensource big data usage, systematically integrate a variety of elements including time, human, resources, scenarios, and organizations in the current cyber-physical-social world, and establish a novel social structure with fair information, equal rights, and a flat configuration. Meanwhile, considering the big modeling gap between the model world and the physical world, the concept of parallel intelligence is introduced. With the help of software-defined everything, parallel intelligence bridges the big modeling gap by means of constructing artificial systems where computational experiments can be implemented to verify social policies, economic strategies, and even military operations. Artificial systems play the role of ＂social laboratories＂ in which decisions are computed before they are executed in our physical society. Afterwards, decisions with the expected outputs are executed in parallel in both the artificial and physical systems to interactively sense, compute, evaluate and adjust system behaviors in real-time, leading system behaviors in the physical system converging to those proven to be optimal in the artificial ones. Thus, the smart guidance and management for our society can be achieved.

Some Remarks about the Deployment of Floating PV Systems in Brazil

Floating photovoltaic systems installed in water bodies such as natural lakes or dams reservoirs, have attracted increased worldwide attention since 2011 and have already been deployed in several countries, including Japan, South Korea and USA. In Brazil, pilot-projects were announced in the reservoirs of hydroelectric power plants of Balbina （State of Amazonas） and Sobradinho （State of Bahia）. Several advantages, not necessarily valid in Brazil, are mentioned for deploying this kind of technology, such as an increase in energy generation, reduction of water losses through evaporation, low environmental impact, no occupation of land etc. In this article, several of these allegations are analyzed preliminarily under the Brazilian point of view, and relevant considerations are presented. It is concluded that the technical and economic advantages of floating photovoltaic systems are not yet clear in Brazil and that pilot projects, such as those under way, should be used to clarify several important aspects related to them.

Mathematical Study of A Memory Induced Biochemical System

In this work, to study the effect of memory on a bi-substrate enzyme kinetic reaction, we have introduced an approach to fractionalize the system, considering it as a threecompartmental model. Solutions of the fractionalized system are compared with the corresponding integer-order model. The equilibrium points of the fractionalized system are derived analytically. Their stability properties are discussed from numerical aspect. We determine the changes of the substances due to the changes of "memory effect". The effect is discussed critically from the perspective of product formation. We have also analyzed the memory induced system with a control measure in view of optimizing the product. Our numerical result reveals that the solutions of the fractionalized system, when it is free from memory, are in good agreement with the integer-order system.It is noticed that the effect of memory influences the reaction in the forward direction and assists in yielding the product more quickly. However, an extensive use of memory makes the system slower, but introduction of a control input makes the reaction faster. It is possible to overcome the slowness of the reaction due to the undue effect of memory by appropriate use of a control measure.

The Future of Manufacturing： A New Perspective

Many articles have been published on intelligent manufacturing, most of which focus on hardware, soft-ware, additive manufacturing, robotics, the Internet of Things, and Industry 4.0. This paper provides a dif-ferent perspective by examining relevant challenges and providing examples of some less-talked-about yet essential topics, such as hybrid systems, redefining advanced manufacturing, basic building blocks of new manufacturing, ecosystem readiness, and technology scalahility. The first major challenge is to （re-）define what the manufacturing of the future will he, if we wish to： ① raise public awareness of new manufacturing＇s economic and societal impacts, and ② garner the unequivocal support of policy- makers. The second major challenge is to recognize that manufacturing in the future will consist of sys-tems of hybrid systems of human and robotic operators; additive and suhtractive processes; metal and composite materials; and cyher and physical systems. Therefore, studying the interfaces between con- stituencies and standards becomes important and essential. The third challenge is to develop a common framework in which the technology, manufacturing business case, and ecosystem readiness can he eval- uated concurrently in order to shorten the time it takes for products to reach customers. Integral to this is having accepted measures of ＂scalahility＂ of non-information technologies. The last, hut not least, chal-lenge is to examine successful modalities of industry-academia-government collaborations through public-private partnerships. This article discusses these challenges in detail.

Preparation of Aminated Lignin through Etherification and Amination

A new method for the preparation of aminated lignin （AEL） through etherification and amination reaction was presented. Chlorine atoms were ？rstly introduced into lignin through its etheri？cation with epichlorohydrin. Then, hydrophilic amine groups were grafted to the modi？ed lignin structure through amination with ethylenediamine to obtain AEL. Subsequent acidi？cation of AEL led to the ionized aminated lignin （IAEL）. The results of our analyses showed that the nitrogen content of AEL was 6.9%. Foaming and emulsifying experiments indicated that AEL had better foamability and emulsifying properties than IAEL. Surface tension tests showed that AEL and IAEL had similar critical micelle concentration （CMC）. However, IAEL had lower surface tension （36.33 mN/m） than AEL （42.89 mN/m） at CMC. These results demonstrate the promising applicability of AEL as an emulsi？er and that of IAEL as feedstock in the production of detergent and dispersant.

A narrative review of the success of intramuscular gluteal injections and its impact in psychiatry

There are 12 billion injections given worldwide every year. For many injections, the intramuscular route is favoured over the subcutaneous route due to the increased vascularity of muscle tissue and the corresponding increase in the bioavailability of drugs when administered intramuscularly. This paper is a review of the variables that affect the success of intramuscular injections and the implications that these success rates have in psychiatry and general medicine. Studies have shown that the success rates of intended intramuscular injections vary between 32 and 52%, with the rest potentially resulting in inadvertent subcutaneous drug deposition. These rates are found to be even lower for certain at-risk populations, such as obese patients and those on antipsychotic medications. The variables associated with an increased risk of injection failure include female sex, obesity, site of injection, and subcutaneous fat depth. New guidelines and methods are needed in order to address this challenge and ensure that patients receive optimum care. Looking forward, the best way to improve the delivery of intramuscular injections worldwide is to develop uniform algorithms or innovative medical devices to confirm or guarantee successful delivery at the bedside.

Middleware technologies for cloud of things： a survey

The next wave of communication and applications will rely on new services provided by the Internet of Things which is becoming an important aspect in human and machines future. IoT services are a key solution for providing smart environments in homes, buildings, and cities. In the era of massive number of connected things and objects with high growth rate, several challenges have been raised, such as management, aggregation, and storage for big produced data. To address some of these issues, cloud computing emerged to the IoT as Cloud of Things （COT）, which provides virtually unlimited cloud services to enhance the large-scale IoT platforms. There are several factors to be considered in the design and implementation of a CoT platform. One of the most important and challenging problems is the heterogeneity of different objects. This problem can be addressed by deploying a suitable ＂middleware＂ which sits between things and applications as a reliable platform for communication among things with different interfaces, operating systems, and architectures. The main aim of this paper is to study the middleware technologies for CoT. Toward this end, we first present the main features and characteristics of middlewares. Next, we study different architecture styles and service domains. Then, we present several middlewares that are suitable for CoT-based platforms and finally, a list of current challenges and issues in the design of CoT-based middlewares is discussed.