Meta-governance is Earth system governance for dealing with the global commons. This article develops a whole network approach to meta-governance to explore the potential for collective action for sustainable development by a loosely coupled network of networks. Networked corporate social responsibility governance has emerged around corporate sustainability and responsibility in the first years of the 21st century. Growing agreements and interactions among CSR initiatives suggest the development, structure, and governance of networked CSR governance as a network (...) that can analytically be viewed as a whole and as a platform for learning about systemic change. Using the evolution of CSR initiatives from about 1990 to 2014, the authors differentiate four developmental stages: independent and fragmented multistakeholder networks as CSR governance, collaborative CSR governance, networked CSR governance, and integrated networked CSR governance. The authors then present a framework to analyze networked CSR governance as a whole network experimenting with meta-governance. (shrink)

Deep convolutional networks exceed humans in sensitivity to local image properties, but unlike biological vision systems, do not discover and encode abstract relations that capture important properties of objects and events in the world. Coupling network architectures with additional machinery for encoding abstract relations will make deep networks better models of human abilities and more versatile and capable artificial devices.

We investigated how the structure of the brain network relates to the stability of perceptual alternation in binocular rivalry. Historically, binocular rivalry has provided important new insights to our understandings in neuroscience. Although various relationships between the local regions of the human brain structure and perceptual switching phenomena have been shown in previous researches, the global organization of the human brain structural network relating to this phenomenon has not yet been addressed. To approach this issue, we reconstructed fiber-tract (...) bundles using diffusion tensor imaging and then evaluated the correlations between the speeds of perceptual alternation and fractional anisotropy (FA) values in each fiber-tract bundle integrating among 84 brain regions. The resulting comparison revealed that the distribution of the global organization of the structural brain network showed positive or negative correlations between the speeds of perceptual alternation and the FA values. First, the connections between the subcortical regions stably were negatively correlated. Second, the connections between the cortical regions mainly showed positive correlations. Third, almost all other cortical connections that showed negative correlations were located in one central cluster of the subcortical connections. This contrast between the contribution of the cortical regions to destabilization and the contribution of the subcortical regions to stabilization of perceptual alternation provides important information as to how the global architecture of the brain structural network supports the phenomenon of binocular rivalry. (shrink)

Networks and the World Wide Web seem to provide an answer to efficiently creating and disseminating knowledge resources. Knowledge, however, is ambiguous in character, and contains both explicit (information) and tacit dimensions - the latter being difficult to value as well as to transfer. Participant identity, commitment and behaviour within the network also affect the sharing of knowledge. Hence, existing laws and norms (including property rights) which have been established on the basis of discrete transactions and monetary value-oriented exchange (...) may not be adequate to deal with the whole spectrum of knowledge transfer. A model is needed to address transfer across a large heterogeneous network. We introduce the concept of sub-networks where tacit knowledge resides and argue that considering social norms underlying trust and other informal mechanisms provides a more suitable basis for understanding the exchange of tacit knowledge. Norm establishment is complicated by the fact that values differ across cultures; however, the social norms that underpin sub-networks can sustain knowledge transfer within them. The purpose of this conceptual article is to introduce the concept of sub-networks and to identify the sub-network/network relationship as an area in which it is necessary to look beyond property rights and raise the issue of norms. We believe that an analysis of the role of social norms in knowledge sub-networks and their interaction with global networks points to a key element in understanding networks and any emerging theory of network ethics in the twenty-first century. (shrink)

In this article, network science is discussed from a methodological perspective, and two central theses are defended. The first is that network science exploits the very properties that make a system complex. Rather than using idealization techniques to strip those properties away, as is standard practice in other areas of science, network science brings them to the fore, and uses them to furnish new forms of explanation. The second thesis is that network representations are particularly helpful (...) in explaining the properties of non-decomposable systems. Where part-whole decomposition is not possible, network science provides a much-needed alternative method of compressing information about the behavior of complex systems, and does so without succumbing to problems associated with combinatorial explosion. The article concludes with a comparison between the uses of network representation analyzed in the main discussion, and an entirely distinct use of network representation that has recently been discussed in connection with mechanistic modeling. (shrink)

During the last decade, Network Science has become one of the most active fields in applied physics and mathematics, since it allows the analysis of a diversity of social, biological and technological systems [24]. From the diversity of applications of Network Science, in this Opinion paper we are concerned about its potential to analyse one of the most extended group sports, Football (soccer in U.S. terminology) [29], since it allows addressing different aspects of the team organization and performance (...) not captured by classical analyses based on the performance of individual players. The reason behind relies on the complex nature of the game, which, paraphrasing the foundational paradigm of complexity sciences “can not be analysed by looking at its components (i.e., players) individually but, on the contrary, considering the system as a whole” or, in the classical words of after-match interviews “it’s not just me, it’s the team”. The recent ability of obtaining datasets of all events occurring during a match, including the position of the players and the interactions between them has opened the door to new kind of studies where it is possible to analyse and quantify the behaviour of a team as a whole, together with the role of a single player [17]. Under this framework, the organization of a team can be considered as the result of the interaction between its players, creating a network based on passes. In this way, we can create passing networks, which are directed (i.e.,... (shrink)

Simion and Kelp develop the obligation-based account of trustworthiness as a compelling general account of trustworthiness and then apply this account to various instances of AI. By doing so, they explain in what way any AI can be considered trustworthy, as per the general account. Simion and Kelp identify that any account of trustworthiness that relies on assumptions of agency that are too anthropocentric, such as that being trustworthy, must involve goodwill. I argue that goodwill is a necessary condition for (...) being trustworthy and further suggest a network account of trustworthy AI, which retains the goodwill as the essential requirement for the concept of trustworthiness and meanwhile predicts that current AI can be trustworthy. The alternative account suggests that the focus of trustworthy AI is not merely AI technology, but the whole network of AI involving AI technology, AI designers, AI companies, and other social and legal institutions. A trustworthy AI requires that AI technology is reliable and that other involved agents are trustworthy. (shrink)

In this post‐sequencing era, geneticists can focus on functional genomics on a much larger scale than ever before. One goal is the discovery and elucidation of the intricate genetic networks that co‐ordinate transcriptional activation in different regulatory circuitries. High‐throughput gene expression measurement using DNA arrays has thus become routine strategy. This approach, however, does not directly identify gene loci that belong to the same regulatory group; e.g., those that are bound by a common (set of) transcription factor(s). Working in yeast, (...) two groups have recently published an elegant method that could circumvent this problem, by combining chromatin immunoprecipitation and DNA microarrays.(1,2) The method is likely to provide a powerful tool for the dissection of global regulatory networks in eukaryotic cells. BioEssays 23:473–476, 2001. © 2001 John Wiley & Sons, Inc. (shrink)

The increasing frequency and scope of financial crises has made global financial stability one of the major concerns of economic policy and decision makers. Under this highly complex environment, supervision of the financial system has to be thought of as a systemic task, focusing not only on the strength of the institutions but also on the interdependent relations among them, unraveling the structure and dynamic of the system as a whole. In recent years, network science has emerged as (...) a leading tool for the investigation of complex systems. Here we review several applications of network science in finance and economics, and discuss existing challenges and future directions which will substantiate network science as a key tool for financial academics, practitioners, and policy and decision makers. (shrink)

Ideas of ‘distributed mind’ are invaluable to archaeology in explaining the intimate involvement of artefacts in human cognition. Much of the work in this domain, however, focuses on proximate interactions of very limited numbers of individuals and artefacts. This chapter argues that people need to broaden the understanding of distributed mind to encompass whole assemblages of artefacts spread across space and time; and that these assemblages can be best conceptualized as networks in which both objects and people are enfolded (...) and enacted. While such networks may exist to some extent in the Palaeolithic and Neolithic eras, it is with the Bronze Age that they really come to the fore, extending the scale of human action beyond the proximate like never before. Examples of this extensive socio-material differentiation are taken from the Aegean Bronze Age, with a focus on pottery. (shrink)

Neurofeedback is a complex learning scenario, as the task consists of trying out mental strategies while processing a feedback signal that signifies activation in the brain area to be self-regulated and acts as a potential reward signal. In an attempt to dissect these subcomponents, we obtained whole-brain networks associated with efficient self-regulation in two paradigms: parallel, where the task was performed concurrently, combining feedback with strategy execution; and serial, where the task was performed consecutively, separating feedback processing from strategy (...) execution. Twenty participants attempted to control their anterior midcingulate cortex using functional magnetic resonance imaging NF in 18 sessions over 2 weeks, using cognitive and emotional mental strategies. We analyzed whole-brain fMRI activations in the NF training runs with the largest aMCC activation for the serial and parallel paradigms. The equal length of the strategy execution and the feedback processing periods in the serial paradigm allows a description of the two task subcomponents with equal power. The resulting activation maps were spatially correlated with functionally annotated intrinsic connectivity brain maps. Brain activation in the parallel condition correlates with the basal ganglia network, the cingulo-opercular network, and the frontoparietal control network ; brain activation in the serial strategy execution condition with the default mode network, the FPCN, and the visual processing network; while brain activation in the serial feedback processing condition predominantly with the CON, the DMN, and the FPCN. Additional comparisons indicate that BG activation is characteristic to the parallel paradigm, while supramarginal gyrus and superior temporal gyrus activations are characteristic to the serial paradigm. The multifaceted view of the subcomponents allows describing the cognitive processes associated with strategy execution and feedback processing independently in the serial feedback task and as combined processes in the multitasking scenario of the conventional parallel feedback task. (shrink)

Delay discounting is a common phenomenon in daily life, which refers to the subjective value of a future reward decreasing as a function of time. Previous studies have identified several cortical regions involved in delay discounting, but the neural network constructed by the cortical regions of delay discounting is less clear. In this study, we employed resting-state functional magnetic resonance imaging (RS-fMRI) to measure the spontaneous neural activity in a large sample of healthy young adults and used the Monetary (...) Choice Questionnaire to directly measure participants’ level of delay discounting. To identify the neural network of delay discounting at rest, we used an individual difference approach to explore brain regions whose spontaneous activities were related to delay discounting across the whole brain. Then, these brain regions served as seeds to identify the neural network of delay discounting. We found that the fractional amplitude of low-frequency fluctuations (fALFF) of the left insula were positively correlated to delay discounting. More importantly, its connectivity to the anterior cingulate cortex was read out for participants’ behavioral performance in the task of delay discounting. In short, our study provides empirical evidence that insula-anterior cingulate cortex connectivity may serve as a part of the neural network for delay discounting. (shrink)

An integrated representation of large‐scale space, or cognitive map, colled PLAN, is presented that attempts to address a broader spectrum of issues than has been previously attempted in a single model. Rather than examining way‐finding as a process separate from the rest of cognition, one or the fundamental goals of this work is to examine how the wayfinding process is integrated into general cognition. One result of this approach is that the model is “heads‐up,” or scene‐based, because it takes advantage (...) of the properties of the human visual system and, particularly, the visual system's split into two pathways. The emphasis on the human location or “where” system is new to cognitive mapping and is port of an attempt to synthesize prototype theory, associative networks and location together in a connectionist system. Not all of PLAN is new, however. Many of its parts have analogues in one or another preexisting theory. What makes PLAN unique is integrating the various components into a coherent whole, and the capacity of this resulting system to speak to a wide range of constraints. Our approach emphasizes adaptiveness; thus, our focus on such issues as ease of use and efficiency of learning. The result is a model that has a stronger relationship both to the environment, and to the ways that humans interact with it, compared with previous models. The resulting model is examined in some detail and compared to other systems. (shrink)

Due to the population ageing, building an elderly livable community has become an urgent task of social welfare development. This Public-Private Partnership construction project faces a variety of pressures from its complex stakeholders. Based on the Qingdao elderly livable community construction project, this paper builds up interpretations about its relationship governance by conducting stakeholder analysis. The paper aims to explore the relationship governance mechanism of multiple connections between related stakeholders. On the basis of complex network theory, this paper establishes (...) a stakeholder relationship network model and describes different modes of different stakeholder relationship in the Qingdao construction project. The paper analyzes the optimal decision-making behavior and interaction of different stakeholders, constructs the objective functions of stakeholder relationship network, applies centrality measure and dominant-set clustering to analyze the optimal conditions of the whole network, and finally carries out simulation calculation. The results show that it is feasible and effective to apply network analysis method to the study of stakeholder relationship in Public-Private Partnership construction projects. (shrink)

The idea that intelligence is embedded not only in a single brain network, but instead in a complex, well-optimized system of complementary networks, has led to the development of whole brain network analysis. Using graph theory to analyze resting-state functional MRI data, we investigated the brain graph networks (or brain networks) of high intelligence quotient (HIQ) children. To this end, we computed the “hub disruption index κ”, an index sensitive to graph network modifications. We found significant (...) topological differences in the integration and segregation properties of brain networks in HIQ compared to standard IQ children, not only for the whole brain graph, but also for each hemispheric graph, and for the homotopic connectivity. Moreover, two profiles of HIQ children, homogenous and heterogeneous, based on the differences between the two main IQ subscales (verbal comprehension index (VCI) and perceptual reasoning index (PRI)), were compared. Brain networks changes were more pronounced in the heterogeneous HIQ than in the homogeneous HIQ subgroups. Finally, we found significant correlations between the graph networks’ changes and the full-scale IQ (FSIQ), as well as the subscales VCI and PRI. Specifically, the higher the FSIQ the greater was the brain organization modification in the whole brain, the left hemisphere, and the homotopic connectivity. These results shed new light on the relation between functional connectivity topology and high intelligence, as well as on different intelligence profiles. (shrink)

In response to the lack of research on the online social network structure of athletes, elements of research on the online social network structure of athletes were constructed based on the whole network perspective and through the study of the characteristics of the whole online social network structure of athletes, in order to provide reference for the physical and mental health development of athletes from a new perspective. Data were collected through questionnaires, and several (...) software programs were used to preprocess and analyse the collected data. Through the analysis of the online whole network structure, it was found that the network density of the online support network was generally greater than that of the online discussion network, and athletes still showed stronger practical support demands and behaved more rationally in the process of training and learning life, while from the perspective of the relationship structure, the athletes’ family and classmates’ online support is weaker than that in previous studies; in terms of the whole network, strong relationships still dominate in this population, while attention should be paid to the impact of weak relationships. (shrink)

We investigate cluster-delay synchronization of a directed network possessing cluster structures by designing an intermittent control protocol. Based on Lyapunov stability theory, we proved that synchronization can be realized for oscillators in the same cluster and cluster-delay synchronization can be realized for the whole network. By simplifying the obtained sufficient conditions, we carry out a succinct and utilitarian corollary. In addition, comparative researches are carried out to show the differences and the usefulness of the obtained results with (...) respect to other similar controllers from the recent literature. Finally we provide two numerical examples to show the effectiveness of the control schemes. (shrink)

IntroductionTranscranial direct current stimulation is a noninvasive brain stimulation technique that applied to modulate brain activity and enhance motor recovery. However, the neurobiological substrates underlying the effects of tDCS on brain function remain poorly understood. This study aimed to investigate the central mechanisms of tDCS on improving the athletic performance of male rowing athletes.MethodsTwelve right-handed male professional rowing athletes received tDCS over the left primary motor cortex while undergoing regular training. The resting-state functional magnetic resonance imaging data were acquired before (...) and after tDCS. Measures of amplitude of low-frequency fluctuation and regional homogeneity were calculated and compared between baseline and follow-up, as well as topological measures including global and local efficiency of functional brain networks constructed by graph theoretical analysis.ResultsMale rowing athletes showed increased isokinetic muscle strength of the left knee and left shoulder after tDCS. Increased ALFF values were found in the right precentral gyrus of male rowing athletes after tDCS when compared with those before tDCS. In addition, male rowing athletes showed increased ReHo values in the left paracentral lobule following tDCS. Moreover, increased nodal global efficiency was identified in the left inferior frontal gyrus of male rowing athletes after tDCS.ConclusionThe findings suggested that simultaneous tDCS-induced excitation over the primary motor cortex might potentially improve the overall athletic performance in male rowing athletes through the right precentral gyrus and left paracentral lobule, as well as left inferior frontal gyrus. (shrink)

As a common social network, the SNEM plays an important role in emergency management. Magnitude emergencies are characterized by high complexity and uncertainty, and it is impossible to rely on the government for emergency management alone. We should absorb multiple subjects to build the SNEM and carry out extensive emergency mobilization in the whole society. The SNEM can integrate resources, gather consensus, promote participation, and reduce risks. The analysis of the types, generation mechanism, subject behavior, and strategy selection (...) of the SNEM aid in adopting appropriate mobilization strategy based on magnitude emergencies, achieving the adaptation of the SNEM and emergency scenarios. By constructing the evolutionary game model of the SNEM for magnitude emergencies, taking China as an empirical sample, this paper explores the behavior evolution law and stable strategy of the government, social organizations, and the public. The results showed that the symbiotic SNEM with a positive response of social organizations and the public under the path of high-intensity mobilization by the government is the best strategy combination, and it is conducive to maximizing the emergency joint force. (shrink)

In a criminal trial, a judge or jury needs to reason about what happened based on the available evidence, often including statistical evidence. While a probabilistic approach is suitable for analysing the statistical evidence, a judge or jury may be more inclined to use a narrative or argumentative approach when considering the case as a whole. In this paper we propose a combination of two approaches, combining Bayesian networks with scenarios. Whereas a Bayesian network is a popular tool (...) for analysing parts of a case, constructing and understanding a network for an entire case is not straightforward. We propose an explanation method for understanding a Bayesian network in terms of scenarios. This method builds on a previously proposed construction method, which we slightly adapt with the use of scenario schemes for the purpose of explaining. The resulting structure is explained in terms of scenarios, scenario quality and evidential support. A probabilistic interpretation of scenario quality is provided using the concept of scenario schemes. Finally, the method is evaluated by means of a case study. (shrink)

With the deepening of reform and opening-up, China’s economy has been further developed, but there is still a problem of uneven development. It is of great significance to completely construct China’s economic spatial correlation network, to clarify the role and status of each province in the whole network, and to study the influencing factors of the national spatial economic network. In this paper, we employ the network analysis method to analyze China’s economic development in the (...) past 20 years. Based on the modified gravity model, we construct China’s spatial economic network and explore the network structure from three aspects: the whole network structure feature, characteristics of individual provinces in the network, and block model analysis. The results show that China’s spatial economic network has strong internal cohesion, and the hierarchy of the network is becoming less and less obvious. However, the network density is low, and the overall network relationship still needs to be strengthened. The different levels in economic development illustrate the obvious economic unbalance among provinces. The block model analysis results demonstrated that coastal areas are more attractive to other provinces and are playing an important role in driving China’s economy. Finally, we employ Quadratic Assignment Procedure regression analysis to analyze the influential factors on spatial economic network. Numerical results show that the geographic proximity and the differences in six factors have significant impact on the spatial economic network. Moreover, the influence of these factors on the economic relation among provinces has been gradually strengthened in recent years. (shrink)

Since the SARS crisis in 2003, institutionalized emergency management systems have been established in each government level for improving inter-organizational collaboration in China. Major accidents require participation of public organizations affiliated with multiple government levels, and the lack of collaboration and coordination among the involved organizations within the critical time constraints during the response process is an existing problem. In this research, a case study of examining the intergovernmental and cross-sectoral collaboration for responding to a well-known oil pipeline explosion accident (...) in China by a complex network method is conducted. The aim is to obtain managerial insights in improving the existing emergency management system in a centralized political-administrative context, such as China. A mixed method of data collection is applied to identify the participating organizations and to determine the interaction spanning organizational boundaries in both hierarchical and horizontal dimensions. An emergency response network is built and visualized for representing intergovernmental and interorganizational collaboration during the response process of the major accident by social network analysis tools. The SNA indicators are used to measure quantitatively the network structure at the levels of the whole network, subnetwork, and node. The obstacles of achieving intergovernmental collaboration are found, and managerial suggestions for improving the existing emergency management system are provided. This research indicates that the Chinese government should pay attention to establishing and sustaining partnerships with private and nonprofit organizations and conduct a blend of hierarchical, market, and network principles in fostering collaboration for addressing major accidents. The public organizations in the local government level are shown to be more active than other participators in coordinating their response operations, and their capability should be emphasized for improvement. Additionally, the interactive relationships among specific emergency function groups and between the affected communities and organizations performing emergency command and coordination function should be strengthened. (shrink)

For a multicellular organism to proceed from egg to adult it must: (i) undergo cell division, (ii) differentiate, (iii) remain a unified whole (Ho). These requirements are at right angles to each other. The first two are achieved through hierarchical processes (vertical control) that are relatively well understood, the third through non-hierarchical processes (horizontal control) physiological evidence for which is abundant, though not widely recognized as a form of control. The essay gives an example of a tissue – the (...) skin of a living squid – whose horizontal network properties come to light when nervous (vertical) control is removed. It offers the name homeotaxy or ‘peer conformity’ for the general principle (allied to the community effect, Gurdon 1988) that constrains the parts of the whole to be in the same state within any given layer of the network – where layers correspond to ontogenetic stages in the development of the tissue – and discusses the question of a need and a name for this principle in Biology. (shrink)

Social network theory is an important paradigm of social structure research, which has been widely used in various fields of research. This paper reviews the development process and the latest progress of social network theory research and analyzes the research application of social network. In order to reveal the deep social structure, this paper analyzes the structure of social networks from three levels: microlevel, mesolevel, and macrolevel and reveals the origin, development, perfection, and latest achievements of complex (...) network models. The regular graph model, P1 model, P2 model, exponential random graph model, small-world network model, and scale-free network model are introduced. In the end, the research on the social network structure is reviewed, and social support network and social discussion network are introduced, which are two important contents of social network research. At present, the research on social networks has been widely used in coauthor networks, citation networks, mobile social networks, enterprise knowledge management, and individual happiness, but there are few research studies on multilevel structure, dynamic research, complex network research, whole network research, and discussion network research. This provides space for future research on social networks. (shrink)

Agri-food clusters have generated great interest in recent years and prompted a new wave of research dedicated to ‘Localized Agri-Food Systems’. However, the specific nature of relations between firms who belong to SYALs has rarely been studied. Our purpose is to show how the analysis of company directors’ advice networks helps to better understand the specificity and innovative dynamics of SYALs. Our research was based on a case study in the Biterrois wine growing region of southern France. We conducted a (...) survey to collect information on advice relations between wine cooperative managers, who play a key role in the innovation process toward quality wine. Sociometric analysis of the advice relations, coupled with interviews, led to three main results: the first was that managers simultaneously cooperate on technical projects and compete for business ends. The second was a correlation between the innovations implemented by the cooperatives and the degree of centrality of the managers in the networks, revealing the relational and local conditions of innovations in SYALs. The third was that managers can modify their own network to improve the competitiveness of both their own cooperative and of the SYAL as a whole. In conclusion, we show that advice network analysis is an appropriate tool to describe the relational dimension of SYALs, to better understand their process of innovation, and to help managers improve the collective strategies they apply within the SYAL. (shrink)

Pushing through a logical continuum of closed-to open-system views of organizations necessarily changes the conceptualization of a firm from a strongly bounded entity to a configuration of networks and sub-networks, which exists and operates in a larger systemic network configuration. We unfold a classification of management processes corresponding to views of the firm along the closed/open-systems continuum. We examine ethical issues that are likely to devolve from these classes of management processes, and we suggest typical means by which managers (...) will attempt to control their firms' exposure to such issues. The final class of management processes examined focuses on the achievement of out-comes that are mutually satisfactory in the set of networks and sub-networks that constitute the focal firm, and that support the sustainability of the whole system. The article contributes to organizational theory, business ethics, and computer and information ethics by providing a comprehensive analysis of the impact of managerial views of the firm and of networks - virtual, social, informational - on managerial processes and on our understanding of how business ethics issues are linked to perceptions of what a firm is, does, and can do. (shrink)

This paper investigates the leaderless and leader-follower time-varying formation design and analysis problems for a group of networked agents subject to discontinuous communications. Firstly, a leaderless time-varying formation control protocol is proposed via the intermittent control strategy, where the control input of each agent is constructed by the distributed local state information and formation instructions in the communication time unit, but it is zero in the noncommunication time unit. Then, an explicit formulation of the formation center function is determined to (...) describe the formation movement trajectory of the whole networked agents. Leaderless time-varying formation design and analysis with discontinuous communications are given in the form of linear matrix inequalities. Moreover, the main results of the leaderless cases are extended to the leader-follower cases. Finally, two numerical examples are provided to illustrate the theoretical results of leaderless and leader-follower cases, respectively. (shrink)

Research programs regularly compete to achieve the same goal, such as the discovery of the structure of DNA or the construction of a TEA laser. The more the competing programs share information, the faster the goal is likely to be reached, to society’s benefit. But the “priority rule”-the scientific norm according to which the first program to reach the goal in question must receive all the credit for the achievement-provides a powerful disincentive for programs to share information. How, then, is (...) the clash between social and individual interest resolved in scientific practice? This chapter investigates what Robert Merton called science’s “communist” norm, which mandates universal sharing of knowledge, and uses mathematical models of discovery to argue that a communist regime may be on the whole advantageous and fair to all parties, and so might be implemented by a social contract that all scientists would be willing to sign. (shrink)

Autism spectrum disorder is a group of complex neurodevelopment disorders characterized by altered brain connectivity. However, the majority of neuroimaging studies for ASD focus on the static pattern of brain function and largely neglect brain activity dynamics, which might provide deeper insight into the underlying mechanism of brain functions for ASD. Therefore, we proposed a framework with Hidden Markov Model analysis for resting-state functional MRI from a large multicenter dataset of 507 male subjects. Specifically, the 507 subjects included 209 subjects (...) with ASD and 298 well-matched health controls across 14 sites from the Autism Brain Imaging Data Exchange. Based on the HMM, we can identify the recurring brain function networks over time across ASD and healthy controls. Then we assessed the dynamical configuration of the whole-brain networks and further analyzed the community structure of transitions across the brain states. Based on the 19 HMM states, we found that the global temporal statistics of the specific HMM states were significantly altered in ASD compared to HCs. These specific HMM states were characterized by the activation pattern of default mode network, sensory processing networks [including visual network, auditory network, and sensory and motor network ]. Meanwhile, we also find that the specific modules of transitions between states were closely related to ASD. Our findings indicate the temporal reconfiguration of the brain network in ASD and provide novel insights into the dynamics of the whole-brain networks for ASD. (shrink)

Myelin is required for efficient nerve conduction, but not all axons are myelinated to the same extent. Here we review recent studies that have revealed distinct myelination patterns of different axonal paths, suggesting that myelination is not an all or none phenomenon and that its presence is finely regulated in central nervous system networks. Whereas powerful reductionist biology has led to important knowledge of how oligodendrocytes function by themselves, little is known about their role in neuronal networks. We still do (...) not understand how oligodendrocytes integrate information from neurons to adapt their function to the need of the system. An intricate cross talk between neurons and glia is likely to exist and to determine how neuronal circuits operate as a whole. Dissecting these mechanisms by using integrative systems biology approaches is one of the major challenges ahead. (shrink)

We explore one aspect of the structure of a codified legal system at the national level using a new type of representation to understand the strong or weak dependencies between the various fields of law. In Part I of this study, we analyze the graph associated with the network in which each French legal code is a vertex and an edge is produced between two vertices when a code cites another code at least one time. We show that this (...) network distinguishes from many other real networks from a high density, giving it a particular structure that we call concentrated world and that differentiates a national legal system (as considered with a resolution at the code level) from small-world graphs identified in many social networks. Our analysis then shows that a few communities (groups of highly wired vertices) of codes covering large domains of regulation are structuring the whole system. Indeed we mainly find a central group of influent codes, a group of codes related to social issues and a group of codes dealing with territories and natural resources. The study of this codified legal system is also of interest in the field of the analysis of real networks. In particular we examine the impact of the high density on the structural characteristics of the graph and on the ways communities are searched for. Finally we provide an original visualization of this graph on an hemicyle-like plot, this representation being based on a statistical reduction of dissimilarity measures between vertices. In Part II (a following paper) we show how the consideration of the weights attributed to each edge in the network in proportion to the number of citations between two vertices (codes) allows deepening the analysis of the French legal system. (shrink)

This study is to explore the optimization of the adaptive genetic algorithm in the backpropagation neural network, so as to expand the application of the BPNN model in nonlinear issues. Traffic flow prediction is undertaken as a research case to analyse the performance of the optimized BPNN. Firstly, the advantages and disadvantages of the BPNN and genetic algorithm are analyzed based on their working principles, and the AGA is improved and optimized. Secondly, the optimized AGA is applied to optimize (...) the standard BPNN, and the optimized algorithm is named as OAGA-BPNN. Finally, three different cases are proposed based on the actual scenario of traffic flow prediction to analyse the optimized algorithm on the matrix laboratory platform by simulation. The results show that the average error distribution of the GA-BPNN algorithm is about 1% with small fluctuation range, better calculation accuracy, and generalization performance in contrast to the BPNN. The average output error of the AGA-BPNN fluctuates around 0 and remains in a relatively stable range as a whole in contrast to that of GA-BPNN; the maximum fitness level keeps increasing during the evolution process but approaches the average value in later process, so the population diversity is hard to be guaranteed. The output error of the OAGA-BPNN fluctuates little compared with that of AGA-BPNN, and its maximum fitness continues to increase in the evolution process with guaranteed population diversity. In short, the OAGA-BPNN algorithm can achieve the best performance in terms of calculation accuracy, generalization performance, and population evolution. (shrink)

This report is grounded in several social concepts: First, the primary goal of genetic testing should be to promote the well-being of the child. Second, the recognition that children are part of a network of family relationships supports an approach to potential conflicts that is not adversarial but, rather, emphasizes a deliberative process that seeks to promote the child's well-being within this context. Third, as children grow through successive stages of cognitive and moral development, parents and professionals should be (...) attentive to the child's increasing interest and ability to participate in decisions about his or her own welfare. (shrink)

Male sexual arousal (SA) has been known as a multidimensional experience involving closely interrelated and coordinated neurobehavioral components that rely on widespread brain regions. Recent functional neuroimaging studies have shown relation between abnormal/altered dynamics in these circuits and male sexual dysfunction. However, alterations in the topological1 organization of structural brain networks in male sexual dysfunction are still unclear. Here, we used graph theory2 to investigate the topological properties of large-scale structural brain networks, which were constructed using inter-regional correlations of cortical (...) thickness between 78 cortical regions (subcortical regions were not included due to the used cortical surface model) in 40 patients with psychogenic erectile dysfunction (pED) and 39 normal controls. Compared with normal controls, pED patients exhibited a less optimal global topological organization with reduced global and increased local efficiencies. Our results suggest disrupted neural integration among distant brain regions in pED patients, consistent with previous reports of impaired white matter structure and abnormal functional integrity in pED. Additionally, disrupted global network topology in pED was observed to be primarily relevant to altered subnetwork and nodal properties within the networks mediating the cognitive, motivational and inhibitory processes of male SA, possibly indicating disrupted integration of these networks in the whole brain networks and might account for pED patients’ abnormal cognitive, motivational and inhibitory processes for male SA. In total, our findings provide evidence for disrupted integrity in large-scale brain networks underlying the neurobehavioral processes of male SA in pED and provide new insights into the understanding of the pathophysiological mechanisms of pED. (shrink)

"_The Moment of Complexity_ is a profoundly original work. In remarkable and insightful ways, Mark Taylor traces an entirely new way to view the evolution of our culture, detailing how information theory and the scientific concept of complexity can be used to understand recent developments in the arts and humanities. This book will ultimately be seen as a classic."-John L. Casti, Santa Fe Institute, author of _Gödel: A Life of Logic, the Mind, and Mathematics_ The science of complexity accounts for (...) that inscrutable mix of chaos and order that governs our natural world. Complexity explains how networks emerge and function, how species organize into ecosystems, how stars form into galaxies, and how just a few sequences of DNA can account for so many different life forms. Recently, the idea of complexity has taken the worlds of business and politics by storm. The concept is used to account for phenomena as varied as the behavior of the stock market, the response of voting populations, and the effects of risk management. Even Disney has used complexity theory to manage crowd control at its theme parks. Given the startling development of new information technologies, we now live in a moment of unprecedented complexity, an era in which change occurs faster than our ability to comprehend it. With _The Moment of Complexity_, Mark C. Taylor offers a timely map for this unfamiliar terrain opening in our midst, unfolding an original philosophy through a remarkable synthesis of science and culture. According to Taylor, complexity is not just a breakthrough scientific concept, but the defining quality of the post-Cold War era. The flux of digital currents swirling around us, he argues, has created a new network culture with its own distinctive logic and dynamic. Drawing on resources from information theory and evolutionary biology, Taylor explains the operation of complex adaptive systems in social and cultural processes and captures a whole new zeitgeist in the making. To appreciate the significance of our emerging network culture, he claims, we need not only to understand contemporary scientific and technological transformations, but also to explore the subtle influences of art, architecture, philosophy, religion, and higher education. _The Moment of Complexity_, then, is a remarkable work of cultural analysis on a scale rarely seen today. To follow its trajectory is to learn how we arrived at this critical moment in our culture, and to know where we might head in the twenty-first century. (shrink)

Network neuroscience represents the brain as a collection of regions and inter-regional connections. Given its ability to formalize systems-level models, network neuroscience has generated unique explanations of neural function and behavior. The mechanistic status of these explanations and how they can contribute to and fit within the field of neuroscience as a whole has received careful treatment from philosophers. However, these philosophical contributions have not yet reached many neuroscientists. Here we complement formal philosophical efforts by providing an (...) applied perspective from and for neuroscientists. We discuss the mechanistic status of the explanations offered by network neuroscience and how they contribute to, enhance, and interdigitate with other types of explanations in neuroscience. In doing so, we rely on philosophical work concerning the role of causality, scale, and mechanisms in scientific explanations. In particular, we make the distinction between an explanation and the evidence supporting that explanation, and we argue for a scale-free nature of mechanistic explanations. In the course of these discussions, we hope to provide a useful applied framework in which network neuroscience explanations can be exercised across scales and combined with other fields of neuroscience to gain deeper insights into the brain and behavior. (shrink)

This paper presents a view of nature as a network of infocomputational agents organized in a dynamical hierarchy of levels. It provides a framework for unification of currently disparate understandings of natural, formal, technical, behavioral and social phenomena based on information as a structure, differences in one system that cause the differences in another system, and computation as its dynamics, i.e. physical process of morphological change in the informational structure. We address some of the frequent misunderstandings regarding the natural/morphological (...) computational models and their relationships to physical systems, especially cognitive systems such as living beings. Natural morphological infocomputation as a conceptual framework necessitates generalization of models of computation beyond the traditional Turing machine model presenting symbol manipulation, and requires agent-based concurrent resource-sensitive models of computation in order to be able to cover the whole range of phenomena from physics to cognition. The central role of agency, particularly material vs. cognitive agency is highlighted. (shrink)

This contribution deals with taking up the challenge of sustainable development through human centred systems which aim at the creation and repatriation of global quality in each society, and which are seen to operate as a whole, on a local, regional or even a planetary scale. The paper argues that, particularly in a field such as information, communication, environment, technological processes and innovations, which have structurally revolutionised first of all manufacturing but also education and daily living at the same (...) time. However, producing new pathogenous structures require, by necessity, a political ecology in order to relate these fields to new figures of meditation/mediance and crossbreeding built up by associative networks. PRELUDE'S experience, as an international networking programme of scientists pursuing with other social factors objectives of codevelopments (in response to the failure of bad development in the North and in the South), and its contribution to the theme Global Perspective 2010 of the CE-FAST Programme suggest the actual relevance and, turning to the future, the decisive function of associative networks as a way of approaching more efficiently, because of their flexibility, complex, highly heterogeneous situations to be tackled in a systemic and global fashion. In complementing institutions and established companies these networks give their new performances and efficacity to institute, and so doing displace acquired balances, and increase their capacity to innovate. (shrink)

We describe and try to motivate our project to build systems using both a knowledge based and a neural network approach. These two approaches are used at different stages in the solution of a problem, instead of using knowledge bases exclusively on some problems, and neural nets exclusively on others. The knowledge base (KB) is defined first in a declarative, symbolic language that is easy to use. It is then compiled into an efficient neural network (NN) representation, run, (...) and the results from run time and (eventually) from learning are decompiled to a symbolic description of the knowledge contained in the network. After inspecting this recovered knowledge, a designer would be able to modify the KB and go through the whole cycle of compiling, running, and decompiling again. The central question with which this project is concerned is, therefore, How do we go from a KB to an NN, and back again? We are investigating this question by building tools consisting of a repertoire of language/translation/network types, and trying them on problems in a variety of domains. (shrink)

In the multidisciplinary field of developmental cognitive neuroscience, statistical associations between levels of description play an increasingly important role. One example of such associations is the observation of correlations between relatively common gene variants and individual differences in behavior. It is perhaps surprising that such associations can be detected despite the remoteness of these levels of description, and the fact that behavior is the outcome of an extended developmental process involving interaction of the whole organism with a variable environment. (...) Given that they have been detected, how do such associations inform cognitive-level theories? To investigate this question, we employed a multiscale computational model of development, using a sample domain drawn from the field of language acquisition. The model comprised an artificial neural network model of past-tense acquisition trained using the backpropagation learning algorithm, extended to incorporate population modeling and genetic algorithms. It included five levels of description—four internal: genetic, network, neurocomputation, behavior; and one external: environment. Since the mechanistic assumptions of the model were known and its operation was relatively transparent, we could evaluate whether cross-level associations gave an accurate picture of causal processes. We established that associations could be detected between artificial genes and behavioral variation, even under polygenic assumptions of a many-to-one relationship between genes and neurocomputational parameters, and when an experience-dependent developmental process interceded between the action of genes and the emergence of behavior. We evaluated these associations with respect to their specificity, to their developmental stability, and to their replicability, as well as considering issues of missing heritability and gene–environment interactions. We argue that gene–behavior associations can inform cognitive theory with respect to effect size, specificity, and timing. The model demonstrates a means by which researchers can undertake multiscale modeling with respect to cognition and develop highly specific and complex hypotheses across multiple levels of description. (shrink)

In typical development, word learning goes from slow and laborious to fast and seemingly effortless. Typically developing 2-year-olds seem to intuit the whole range of things in a category from hearing a single instance named—they have word-learning biases. This is not the case for children with relatively small vocabularies. We present a computational model that accounts for the emergence of word-learning biases in children at both ends of the vocabulary spectrum based solely on vocabulary structure. The results of Experiment (...) 1 show that late-talkers' and early-talkers' noun vocabularies have different structures and that neural networks trained on the vocabularies of individual late talkers acquire different word-learning biases than those trained on early-talker vocabularies. These models make novel predictions about the word-learning biases in these two populations. Experiment 2 tests these predictions on late- and early-talking toddlers in a novel noun generalization task. (shrink)

Multicultural environments require learning multiple number notations wherein some are encountered more frequently than others. This leads to differences in exposure and consequently differences in usage between notations. We find that differential notational usage imposes a significant neurocognitive load on number processing. Despite simultaneous acquisition, forty-two adult binumerate populations, familiar with two positional writing systems namely Hindu Nagari digits and Hindu Arabic digits, reported significantly lower preference and usage for Nagari as compared to Arabic. Twenty-four participants showed significantly increased reaction (...) times and reduced accuracy while performing magnitude comparison tasks in Nagari with respect to Arabic. Functional magnetic resonance imaging revealed that processing Nagari elicited significantly greater activity in number processing and attention networks. A direct subtraction of networks for Nagari and Arabic notations revealed a neural circuit comprising of bilateral intra-parietal sulcus, inferior and mid frontal gyri, fusiform gyrus and the anterior cingulate cortex (FDR p<0.005). Additionally, whole brain correlation analysis showed that activity in the left inferior parietal region was modulated by task performance in Nagari. We attribute the increased activation in Ng to increased task difficulty due to infrequent exposure and usage. Our results reiterate the role of the left intra-parietal sulcus in modulating performance in numeric tasks and highlight that of the attention network for monitoring symbolic notation mode in binumerates. (shrink)

In a complex network, each edge has different functions on controllability of the whole network. A network may be out of control due to failure or attack of some specific edges. Bridges are a kind of key edges whose removal will disconnect a network and increase connected components. Here, we investigate the effects of removing bridges on controllability of network. Various strategies, including random deletion of edges, deletion based on betweenness centrality, and deletion based (...) on degree of source or target nodes, are used to compare with the effect of removing bridges. It is found that the removing bridges strategy is more efficient on reducing controllability than the other strategies of removing edges for ER networks and scale-free networks. In addition, we also found the controllability robustness under edge attack is related to the average degree of complex networks. Therefore, we propose two optimization strategies based on bridges to improve the controllability robustness of complex networks against attacks. The effectiveness of the proposed strategies is demonstrated by simulation results of some model networks. These results are helpful for people to understand and control spreading processes of epidemic across different paths. (shrink)

Objectives: Pediatric cancer is a life-threatening disease that poses significant challenges to the life of all family members (diagnosed child, parents, siblings) and the family as a whole. To date, limited research has investigated family adjustment when facing pediatric cancer. The aim of the current longitudinal study was to explore the predictive role of protective factors at the individual (parental psychological flexibility), intrafamilial (dyadic coping) and contextual level (network support) in explaining family adjustment as perceived by parents of (...) children with leukemia or non-Hodgkin lymphoma. In addition, we were interested to see whether these protective factors could be predictive for family adjustment at a later time point. Method: Participants were 70 mothers and 53 fathers (80 families) of children with leukemia or non-Hodgkin lymphoma. Mean time since diagnosis was 5.26 (T1) and 18.86 (T2) months post-diagnosis. Parents completed the Acceptance and Action Questionnaire II (to assess psychological flexibility), Dyadic Coping Inventory, a network support questionnaire, Impact on Family Scale and the Family Adjustment Scale. Both concurrent and prospective association models were tested. Results: Psychological flexibility, dyadic coping and network support proved to be cross-sectionally and positively related to parents’ perception of family adjustment post-diagnosis; psychological flexibility and dyadic coping proved to predict better family adjustment over time. Conclusions: Our findings led to the conclusion that protective factors at all three levels (individual, intrafamilial and contextual) are important for explaining family adjustment as perceived by parents facing a diagnosis of cancer in their child. Interventions targeting the individual, couple, as well as family level are warranted to enhance family adjustment. (shrink)

NEMO means Network Mobility which is the extension of Mipv6 and it is invented for accessing internet for the group of people when they are travelling in Vehicle as Network group. During handoff while exchanging Binding Updates between the Mobile Network Node, Correspondent Node and Home Agent, many security threats are present during those messages exchange. It may prone to several standard malicious attacks on the BU and Binding Acknowledgement. An efficient end-to-end security method is required to (...) protect the BU Exchange between MNN, HA and CN. In this paper, a secure architecture is proposed to provide authentication and confidentiality at each level of communication using a 3-Party Key Exchange called 3-PKE-NEMO with the help of Bilinear Pairing Theorem. Handoff delay is reduced without compromising security strength. The whole experimentation of this proposed work is carried out using NS2 simulation tool and authentication proof is given using BAN logic between all the nodes in NEMO. The proposed security architecture is compared with related existing solutions and found to be more secure. (shrink)

Diffusion in social networks is a result of agents’ natural desires to conform to the behavioral patterns of their peers. In this article we show that the recently proposed “propositional opinion diffusion model” could be used to model an agent’s conformity to different social groups that the same agent might belong to, rather than conformity to the society as whole. The main technical contribution of this article is a sound and complete logical system describing the properties of the influence (...) relation in this model. The logical system is an extension of Armstrong’s axioms from database theory by one new axiom that captures the topological structure of the network. (shrink)

How can our societies be stabilized in a crisis? Why do we enjoy and understand Shakespeare? Why are fruitflies uniform? How do omnivorous eating habits aid our survival? What makes the Mona Lisa's smile beautiful? How do women keep their social structures intact? -- Could there possibly be a single answer to all these questions? This book shows that the statement 'weak links stabilize complex systems' provides the key to understanding each of these intriguing puzzles, and many others too. The (...) author...uses weak (low affinity, low probability) interactions as a thread to introduce a vast variety of networks from proteins to economics and ecosystems. --From publisher description. (shrink)

Antifragility is a property from which systems are able to resist stress and furthermore benefit from it. Even though antifragile dynamics is found in various real-world complex systems where multiple subsystems interact with each other, the attribute has not been quantitatively explored yet in those complex systems which can be regarded as multilayer networks. Here we study how the multilayer structure affects the antifragility of the whole system. By comparing single-layer and multilayer Boolean networks based on our recently proposed (...) antifragility measure, we found that the multilayer structure facilitated the production of antifragile systems. Our measure and findings will be useful for various applications such as exploring properties of biological systems with multilayer structures and creating more antifragile engineered systems. (shrink)