Self-organizing Feature Research Articles

Diffraction pattern of Bacillus subtilis CotY spore coat protein 2D crystals

Bacillus subtilis spore coat is a bacterial proteinaceous structure with amazing characteristics of self-organization, unique resiliency, toughness and flexibility in the same time. The spore coat represents a complex multilayered protein structure which is composed of over 80 coat proteins. Some of these proteins form two dimensional crystal structures who’s low resolution ternary structure as was determined by electron microscopy. However, there are no 3D structure of these proteins known, due to a problem of preparing 3D crystals which could be analyzed by synchrotron X-ray sources. In the present study, Grazing-Incidence Wide-Angle X-ray Scattering (GIWAXS) was applied to investigate a diffraction pattern of CotY 2D crystals formed on Langmuir monolayer films. We observed two distinct diffraction rings and their position corresponds to a structure with the lattice spacing of 10.6 Å and 5.0 Å, respectively. Obtaining diffractions of 2D crystals pave the way to determination of 3D structure of coat proteins by using strong X-ray sources.

A Novel Single-Wire Power Transfer Method for Wireless Sensor Networks

Wireless sensor networks (WSNs) have broad application prospects due to having the characteristics of low power, low cost, wide distribution and self-organization. At present, most the WSNs are battery powered, but batteries must be changed frequently in this method. If the changes are not on time, the energy of sensors will be insufficient, leading to node faults or even networks interruptions. In order to solve the problem of poor power supply reliability in WSNs, a novel power supply method, the single-wire power transfer method, is utilized in this paper. This method uses only one wire to connect source and load. According to the characteristics of WSNs, a single-wire power transfer system for WSNs was designed. The characteristics of directivity and multi-loads were analyzed by simulations and experiments to verify the feasibility of this method. The results show that the total efficiency of the multi-load system can reach more than 70% and there is no directivity. Additionally, the efficiencies are higher than wireless power transfer (WPT) systems under the same conductions. The single-wire power transfer method could satisfy the characteristics of WSNs and effectively solve the problem of poor power supply reliability.

Enhancing the effectiveness of multi-agent cooperation for green manufacturing: Dynamic co-evolution mechanism of a green technology innovation system based on the innovation value chain

A virtuous cycle of the green technology innovation (GTI) system (GTIS) can not only effectively serve GTI subjects in the system but also fully improve green manufacturing and reduce environmental pollution. The essence of the GTIS evolution of manufacturing enterprises (MEs) under multi-agent cooperation (MEUMAC) is encouraged by governments and led by MEs, which jointly promote the process of GTIS from low-end to high-end through interaction with universities, research institutions, supply chains, intermediaries and consumers. MEs cooperate with multiple GTI subjects to continuously improve the GTI level of MEUMAC, and the subsystems of the GTIS interact and coordinate dynamically. To promote the upgrade of the GTIS under multi-agent cooperation, the dynamic co-evolution mechanism of the GTIS needs to be explored. Innovation process is a value chain that transforms from knowledge creation to product promotion based on the innovation value chain. Based on system theory, this process can be solved through five parts: input, processing, output, feedback and upgrade. The structure and evolution path of the GTIS were analysed based on the innovation value chain theory and system theory. Logistic symbiotic response system is a typical system with self-organization characteristics, and the development law of the GTIS of MEUMAC is similar with the symbiotic system. Hence, an evolution model based on a Logistic model was constructed to determine state and control variables. The results show that the evolution of the GTIS of MEUMAC is the spatial advancement and temporal evolution of the system under the action of internal and external subjects, which is ultimately manifested as the process of the GTI performance output. The operation status of green technology is a key factor in the dynamic co-evolution of the GTIS of MEUMAC, which is the order parameter of the system. Environmental regulation policies (ERPs) have a strong positive incentive effect on the dynamic co-evolution of the GTIS of MEUMAC. Regarding the current ERPs, the effect intensity of different policies is command regulation, market regulation, public participation regulation and voluntary action regulation. The results of this study not only help MEs to optimize the implementation process of the GTIS and provide practical guidance to formulate ERPs but also extend the theoretical system of co-evolution and enrich the innovation value chain theory.

A review of genetic-based evolutionary algorithms in SVM parameters optimization

Parameters optimization is a research hotspot of SVM and has gained increasing interest from various research fields. Compared with other optimization algorithms, genetic-based evolutionary algorithms that have achieved optimization according to the laws of separation and free combination in genetics are gradually attracted much attention. Also, due to the characteristics of self-organization and self-adaptation, these algorithms often enable SVM to obtain appropriate parameters, so that the model can be applied to more applications. Additionally, many improvements have been proposed in the past two decades in order to allow the optimized SVM model to obtain better performance. This work focuses on reviewing the current state of genetic-based evolutionary algorithms used to optimize parameters of SVM and its variants. First, we introduce the principles of SVM and provide a survey on optimization methods of its parameters. Then we propose a taxonomy of improving genetic-based evolutionary algorithms according to code mechanism, parameters control, population structure, evolutionary strategy, operation mechanism, operators, and many other hybrid approaches. Furthermore, this paper analyzes and compares the advantages and disadvantages of the above algorithms explicitly, and provides their applicable scenarios as well. Finally, we highlight the existing problems of genetic-based evolutionary algorithms used for parameters optimization of SVM and prospect development trends of this field in the future.

Italian tourism intermediaries: a social network analysis exploration

ABSTRACT The purpose of this paper is to analyse the application of Social Network Analysis (SNA) to the Italian tourism system. The research question is: do relationships among tourist enterprises affect the organizational asset of the Italian travel system? The research takes as unit of analysis the Italian travel agencies and tour operators system and represents quite a significant disclosure for organizational theses because it offers a different view over the structure and governance of a hospitality intermediaries’ network. SNA is helpful indetecting genuine proficiency and therefore in foreseeing possible losses determined by poor or inefficient configurations. Furthermore, it will help delineate new roles within the organizational networks and evaluate the relation between formal and informal organizational structures. This paper provides a structural analysis of the Italian travel agencies network and highlights its self-organization characteristics (typical of a complex system) that lead to the development of informal communities. The methods of network science proved useful and effective and, together with more traditional approaches and a qualitative knowledge of the system, can provide a deeper and more extensive understanding of the system.

Photoprogrammable Mesogenic Soft Helical Architectures: A Promising Avenue toward Future Chiro-Optics.

Mesogenic soft materials, having single or multiple mesogen moieties per molecule, commonly exhibit typical self-organization characteristics, which promotes the formation of elegant helical superstructures or supramolecular assemblies in chiral environments. Such helical superstructures play key roles in the propagation of circularly polarized light and display optical properties with prominent handedness, that is, chiro-optical properties. The leveraging of light to program the chiro-optical properties of such mesogenic helical soft materials by homogeneously dispersing photosensitive chiral material into an achiral soft system or covalently connecting photochromic moieties to the molecules has attracted considerable attention in terms of materials, properties, and potential applications and has been a thriving topic in both fundamental science and application engineering. State-of-the-art technologies are described in terms of the material design, synthesis, properties, and modulation of photoprogrammable chiro-optical mesogenic soft helical architectures. Additionally, the scientific issues and technical problems that hinder further development of these materials for use in various fields are outlined and discussed. Such photoprogrammable mesogenic soft helical materials are competitive candidates for use in stimulus-controllable chiro-optical devices with high optical efficiency, stable optical properties, and easy miniaturization, facilitating the future integration and systemization of chiro-optical chips in photonics, photochemistry, biomedical engineering, chemical engineering, and beyond.

Building a Case for Complexity Theory in the Construction of Art Education Curricula

Abstract In building a case for grounding art education curricula in complexity theory as one approach to more meaningful art making, this paper is presented as a freestanding literature review. This review is neither comprehensive nor exhaustive, but is representative of the literature researched. The main purpose of this paper is to provide new perspectives on complexity theory in education, specifically in art education. In the paper, we discuss complexity theory and how it emerged as a theory for understanding soft sciences. Then we explicate the characteristics of self-organization, bottom-up emergence, decentralized network, short-range relationships, nested organization, and being recursive, non-linear, structurally determined, and far-from-equilibrium, which we posit as most conducive to improved curriculum construction. As a means of situating our paper, we end by illustrating how complexity theory has been addressed sparingly in art education to date.

Development of agency traits in adolescents who are on record with their school and the Minors Affairs Department

The problems of minors with juvenile record often pertain to the weakness of their agency. The subject of this research is determination of the agency traits, which are weakest among adolescents who are on record with their school and the Minors Affairs Department, as well as elaboration and scientific substantiation of program for their development. The program developed by the authors can serve as the active means for increasing agency among adolescents with juvenile record. The research included 99 adolescents, 50 of which are currently on record. To measure the agency traits of individuals, the study employed psychodiagnostic questionnaires. Comparison between adolescents with record and those of good social standing revealed their agency traits that require development: mediacy, activeness, autonomy, creativity, responsibility, self-respect and self-esteem, characteristics of self-organization in activity (goal-setting, planning, self-control), qualities of social and communication competence. The program was tested using experimental plan with a control group, as well as measurement before and after exposure. The results yielded statistical confirmation of the effectiveness of all six parts of the program: 1) self-cognition; 2) social competence; 3) self-organization; 4) realization of one’s self in the context of activity, selection of goals, decisions and elimination of contradictions; 5) moral consciousness as an ability to exercise moral choices; 6) realization of one’s self in the context of life, development of awareness and responsibility.

ТЕХНОЛОГИЯ ТАЙМ-МЕНЕДЖМЕНТ КАК СРЕДСТВО АДАПТАЦИИ ВЧЕРАШНЕГО ШКОЛЬНИКА К ОБУЧЕНИЮ В УСЛОВИЯХ УНИВЕРСИТЕТА

School education is different from university education. If at school students are under the care of parents and a team of teachers, then at university students face the need to independently organize their learning activities. This kind of change is embarrassing for many first-year students. This problem is associated with the low level of self-organization of first-year students. In addition to this, self-organization of students has its own character of manifestation in different groups of students. Based on the above, an urgent problem in pedagogical research is a qualitative and quantitative diagnosis of the level of selforganization of first-year students and the search for effective means to increase the level of self-organization of students. Thus, the problem of this study is to identify the existing level of self-organization among first-year students and recommend how to increase the level of selforganization. To diagnose the level of self-organization we used a diagnostic complex created by the author. According to the identified level and characteristics of self-organization, there are given recommendations for increasing the level and quality of self-organization of firstyear students using time management techniques. An increase in the level of self-organization in the experimental group of students in educational activities was revealed. Consequently, the time management technology in the development of students’ organizational skills in educational activities is considered justified and effective self-management.

An improved impedance-based damage classification using Self-Organizing Maps

The identification and severity of structural damages, especially in the early stage, is critical in structural health monitoring (SHM) systems. Among several approaches used to accomplish this goal, the electromechanical impedance (EMI) technique has taken place within non-destructive evaluation (NDE) methods. On the other hand, neural networks (NN) based on self-organizing maps (SOM) has been a promising tool in many engineering classification problems. However, there is a gap of application regarding the combination of the EMI technique and SOM NN. To encourage this, an enhanced EMI-based damage classification method using self-organizing features is proposed in the present research paper. A SOM NN architecture was implemented whose inputs were derived from representative features of the impedance signatures. As a result, self-organizing maps can be used as an effective tool to enhance the damage classification in EMI-based SHM applications. For the present application, the results indicated a promising and useful contribution to the grinding field.

A Complex Networks Approach for Reliability Evaluation of Swarm Systems Under Malicious Attacks

The reliability of swarm systems needs to be investigated because of their self-adaption and self-organized features. Previous studies mainly focused on the reliability of a single agent, whereas for swarm systems, the ability to maintain their overall connection and function under adverse conditions is more important. It remains challenging on how to evaluate the reliability of swarm systems at the system level. In this paper, we present a reliability evaluation method for swarm systems by characterizing the behavior of the whole system using the method of temporal network analysis. A novel comprehensive reliability metric, i.e. cooperation reliability (CR), is proposed, considering both system integrity and motion consensus. Meanwhile, by identifying critical individuals in swarm systems, we design different malicious attack strategies. It is found that the malicious attacks perform much more harmfully to the reliability of swarm systems than noise and random attack. Moreover, we find that the reliability of a swarm system is sensitive to the swarm density in our framework due to the dynamical interaction of the system. Our findings may shed light on understanding the complicated behaviors of swarm systems under attack and designing a more robust swarm system.

Performance evaluation of ad-hoc based aerial monitoring system

Recently there is a huge interest in designing and implementing systems that can be used in surveillance and emergency situations. These systems are designed and implemented using two main technologies that are: Mobile Ad-hoc Networks (MANETs) and the Unmanned Aerial Vehicles (UAVs). MANETs with its unique characteristics of rapid deployment, self-organization and cost effectivenes had made it a popular topic for designers and developers to design and implement such systems. In this paper, a prototype system was designed and implemented using MANETs and UAVs; this system can be developed to be used as an aerial monitoring system in surveillance and security issues, the system was used to record and send a real-time video from source to destination node over a multihop path. This system was first implemented and tested using testbed method, then it was simulated using network simulator (NS-3) with two case studies to evaluate the performance of the system using two routing protocols (Ad-hoc On-Demand Destance Vector AODV[1] and Optimised Link State Routing OLSR [2]). The evaluating metrics used here are; delay, average jitter, packet loss ratio (PLR) and packet delivery factor (PDF) against variable number of nodes. The optained results of the test bed method showed the configuration parameters and self-organization characteristics of MANET, the results obtained from the simulation platform illustrated that the OLSR had outperformed the AODV protocol in dense networks and the optimum number of nodes needed to cover the simulation area were 90 nodes.

An adaptive retransmit mechanism for delay differentiated services in industrial WSNs

The Internet of Things (IoT) is the latest Internet development, with billions of Internet-connected devices and a wide range of industrial applications. Wireless sensor networks are an important part of the Internet of Things. It has received extensive attention from researchers due to its large-scale, self-organizing, and dynamic characteristics and has been widely used in industry, traffic information, military, environmental monitoring, and so on. With the development of microprocessor technology, sensor nodes are becoming more and more powerful, which enables the same wireless sensor networks (WSNs) platform to meet the different quality of service (QoS) requirements of many applications. Applications for industrial wireless sensor networks range from lower physical layers to higher application layers. The same wireless sensor network sometimes needs to process information from different layers. Traditional protocols lack differentiated services and cannot make full use of network resources. In this paper, an Adaptive Retransmit Mechanism for Delay Differentiated Services (ARM-DDS) scheme is proposed to meet different levels of delays of applications. Firstly, we analyze the impact of different retransmit mechanisms and parameter optimization on delays and energy consumption. Based on the results of the analysis, in ARM-DDS scheme, for routes with transmission delay tolerance, energy-saving retransmission mechanisms are used, and low-latency retransmission mechanisms are used for latency-sensitive routes. In this way, the data routing delays of different applications are guaranteed within bound and the energy consumption of the network is reduced. What is more, ARM-DDS scheme makes full use of the residual energy of the network and uses a small delay routing retransmit mechanism in the far-sink area to reduce end-to-end delay. Both theoretical analysis and simulation experiments show that under the premise of the same reliability requirements, ARM-DDS scheme reduces data transmission delay 12.1% and improves network energy utilization 28%. Given that the reliability requirements of the data stream are different, the scheme can also extend the network lifetime.

Enhancement of Security for Cloud Based IoT Using XHE Scheme

Security is a million dollar issue for all computer systems. Every week there is news of another major breakin to a commercial or government system. Also it is well known that many governments are actively engaged in cyber-warfare, trying to break into the systems of other governments and other groups. The Internet of Things is increasingly changing into an omnipresent computing service, requiring vast volumes of knowledge storage and process. Unfortunately, due to the unique characteristics of resource constraints, self-organization and short range communication in IoT, it always resorts to the cloud for outsourced storage and computation. Security is one of the major challenges faced by cloud based IoT. The standard file protection technique relies on password based encryption schemes and they are vulnerable to brute force attacks. The reason is that, for a wrongly guessed key, the decryption process yields an invalid-looking plaintext message, confirming the invalidity of the key, while for the correct key it outputs a valid-looking plaintext message, confirming the correctness of the guessed key. Honey encryption helps to minimise this vulnerability. Hence, this paper proposed an extended Honey Encryption (XHE) scheme for enhancing the security of the cloud based IoT.

Physical length scales of wind-blown snow redistribution and accumulation on relatively smooth Arctic first-year sea ice

Snow thickness measurements over relatively smooth Arctic first-year sea ice, obtained near Cambridge Bay in the Canadian Arctic (2014, 2016 and 2017) and near Elson Lagoon in the Alaskan Arctic (2003 and 2006), are analyzed to quantify physical length-scales and their relevant scaling behaviors. We use the multi-fractal temporally weighted detrended fluctuation analysis method to detect two major physical length-scales from the two independent study locations. Our results suggest that physical processes underlying the formation of snow dunes are consistent and that the wind is the main process shaping the snow thickness variability and redistribution. One scale, around 10 m, appears to be related to the formation of the snow ‘dunes’, while the other scale, between 30 and 100 m, is likely associated with the various interactions of the snow dunes such as merging, calving and lateral linking. Results imply that snow on level sea ice shows self-organized characteristics.

Theoretical and methodological foundations of self-organization of socio-economic systems

The article explores the category of self-organization from the standpoint of a synergistic theoretical paradigm. An explanation of self-organization as a form of the origin, existence and evolution of systems is given. The problems of selforganization of socio-economic systems are specially considered. The features of individual levels of self-organization of the system — macro-, meso-, and microscopic — are revealed. The spatial, temporal and functional structures of self-organization that are characteristic of a synergistic analysis of socio-economic systems are studied, the features of self-organization within these structures are shown. On the basis of the theoretical and methodological foundations of selforganization, some objective requirements are formulated for the general concept of systemic socio-economic reform in Russia.

INJURY RATE FACTORS IN EXTREME SPORTS ATHLETES WITH DIFFERENT MENTAL SELF-REGULATION TYPES

Aim. The article deals with studying the injury rate factors in athletes with different peculia­rities of mental self-regulation. Materials and methods. Male athletes aged 18–32 involved in cross-country motorcycle and bicycle races, snowboarding, and skateboarding participated in the study (n = 167). The following injury factors were taken into account: the number and severity of injuries, length of the recovery period, limitations on doing sport after recovery. The intensity of the following self-organization characteristics was assessed: determination, self-discipline, flexibility, perseverance, commitment to the current aim, and the general level of self-organization. The frequency of using the following mental self-regulation techniques during training and competitions was assessed: autosuggestion, self-persuasion, physical exercises, breathwork, auto-training, psycho-muscular training, motor imagery practice, visualization, and meditation. Results. Athletes with better-developed self-discipline and those practicing psycho-muscular training have fewer injuries while doing extreme sports. The injuries of athletes practicing psycho-muscular training are not so severe. Athletes with better determination and self-discipline recover faster after injuries. This can also be applied to those athletes who often use the techniques of autosuggestion, self-persuasion, psycho-muscular training, meditation, and visualization. Athletes with greater perseverance have fewer limitations on doing sport after recovery. This is also true for athletes practicing autosuggestion, self-persuasion, and meditation. No differences in the injury rate of cross-country motorcyclists, snow- and skateboarders were revealed. Conclusion. It is appropriate to treat the peculiarities of mental self-regulation as a factor affecting the injury rate of athletes practicing extreme sports.

Features of self-organization and biological properties of solutions of citric and succinic acids in low concentrations

A relationship between the nonmonotonic concentration dependences of the size of the dispersed phase (nanoassociates), physicochemical properties (electric conductivity, pH, redox potential), and fertility of hydrobionts under the action of solutions of citric (CA) and succinic (SA) acids in low concentrations was established. Solutions of CA stimulate the fertility of Paramecium caudatum infusoria and Chlorella vulgaris algae in a wide range of formation of domains and nanoassociates (1•10–13–1•10–5 mol L–1), whereas solutions of SA exert almost no effect on the fertility and slightly inhibit it only in a range of nanoassociate formation at the calculated concentrations from 1•10–17 to 1•10–14 mol L–1.

Opinion formation model with co-evolution of individual behavior and social environment

Entering the information era, the formation of public opinion is largely associated with the complex system constructed by the Internet, thereby possessing new characteristics. The formation of public opinion is the result of the interaction of individual behavior with social environment. In reality, the environmental factor and the individual behavior are usually related to each other and co-evolve with time. Based on the Ising model, in this paper established is an opinion formation model that includes the process of the accumulation and digestion of the social tension. In the model, a parameter named effective dissolving factor <i>c</i> is designed to represent the extent of the interaction between the system and the social environment. A two-dimensional dynamical system is involved in the model to describe the dynamics of individual behavior and social tension. The co-evolution behavior of the system is studied. Based on the Landau mean field theory, the stationary states of the dynamical system under different parameter values, i.e. the value of effective dissolving factor <i>c</i>, their stability and bifurcation of the system, are analyzed. Finally, the computer simulation method is used to verify the results. The research shows that with the co-evolution mechanism of the system, our model exhibits certain self-organization characteristics. When the effective dissolving factor <i>c</i> is smaller than the threshold value, the system will reach final consensus opinion, resulting in a macroscopically ordered state. Otherwise, when the dissolving factor <i>c</i> exceeds a threshold value, the system is stable in the disordered state. It is interesting to find that there is such a critical value of the parameter that it leads the system to be self-organized into a critical state from any initial state. The future detailed investigation on the criticality of the co-evolving system is also suggested, such as testing whether the system has evolved into the critical state according to the finite-sized scaling theory and calculating the critical exponent of the system. In addition, in this paper provided is a new perspective to tackle practical problems in public opinion. Based on the mechanism of the formation of public opinion revealed by our model, researchers are encouraged to conduct studies on how to monitor the state of public opinion more precisely and to predict the tipping point of the system evolution.

A Survey on Consensus Mechanisms and Mining Strategy Management in Blockchain Networks

The past decade has witnessed the rapid evolution in blockchain technologies, which has attracted tremendous interests from both the research communities and industries. The blockchain network was originated from the Internet financial sector as a decentralized, immutable ledger system for transactional data ordering. Nowadays, it is envisioned as a powerful backbone/framework for decentralized data processing and data-driven self-organization in flat, open-access networks. In particular, the plausible characteristics of decentralization, immutability and self-organization are primarily owing to the unique decentralized consensus mechanisms introduced by blockchain networks. This survey is motivated by the lack of a comprehensive literature review on the development of decentralized consensus mechanisms in blockchain networks. In this survey, we provide a systematic vision of the organization of blockchain networks. By emphasizing the unique characteristics of incentivized consensus in blockchain networks, our in-depth review of the state-of-the-art consensus protocols is focused on both the perspective of distributed consensus system design and the perspective of incentive mechanism design. From a game-theoretic point of view, we also provide a thorough review on the strategy adoption for self-organization by the individual nodes in the blockchain backbone networks. Consequently, we provide a comprehensive survey on the emerging applications of the blockchain networks in a wide range of areas. We highlight our special interest in how the consensus mechanisms impact these applications. Finally, we discuss several open issues in the protocol design for blockchain consensus and the related potential research directions.