Research on Authors\u27 Co-authorship Network in Supply Chain Finance in China Based on Social Network Analysis

This paper used social network analysis method to analyze the high frequency author-co-author network in domestic supply chain finance field. In this study, relevant literatures on supply chain finance collected by CNKI from 2005 to 2019 were selected and key information was extracted. This paper used SATI, the literature citations information statistical analysis tool, to build correlation matrix. Social network analysis software UCINET was used to draw the map of co-authored network. The authors\u27 subnet patterns, network density, centrality, cohesive subgroups and structural holes were analyzed, and the scientific collaboration network characteristics in this field were elaborated to promote academic exchange and development in the field of supply chain finance. The analysis results showed that the authors of supply chain finance in China is not connected enough, the overall network connectivity is weak, and there are few core nodes that play a key role. Therefore, scholars in this field should strengthen cooperation appropriately in the future

Topological Cluster Analysis Reveals the Systemic Organization of the Caenorhabditis elegans Connectome

The modular organization of networks of individual neurons interwoven through synapses has not been fully explored due to the incredible complexity of the connectivity architecture. Here we use the modularity-based community detection method for directed, weighted networks to examine hierarchically organized modules in the complete wiring diagram (connectome) of Caenorhabditis elegans (C. elegans) and to investigate their topological properties. Incorporating bilateral symmetry of the network as an important cue for proper cluster assignment, we identified anatomical clusters in the C. elegans connectome, including a body-spanning cluster, which correspond to experimentally identified functional circuits. Moreover, the hierarchical organization of the five clusters explains the systemic cooperation (e.g., mechanosensation, chemosensation, and navigation) that occurs among the structurally segregated biological circuits to produce higher-order complex behaviors

Analysis of orthopaedic device development in South Africa: Mapping the landscape and understanding the drivers of knowledge development and knowledge diffusion through networks

An orthopaedic medical device refers to a part, implant, prosthetic or orthotic which is used to address damage to the body's musculoskeletal system, primarily by providing stability and mobility. Orthopaedic medical devices play a role in injury-related disorders, which have been highlighted as a key element of the quadruple burden of disease in South Africa. In this thesis, orthopaedic devices are conceptualised as a technological field and a technological innovation system (TIS) framework is applied to understand orthopaedic device development in South Africa. Knowledge development and knowledge diffusion are fundamental components of any innovation system. The thesis hypothesises that the functions “knowledge development” and “knowledge diffusion through networks” of the orthopaedic devices TIS are influenced by contextual factors. The objectives of the study are: to identify the actors who generate knowledge for orthopaedic device development and to characterise the relationships between them; to identify focus areas of orthopaedic device development; to provide insight into the drivers and barriers to knowledge development and diffusion in the TIS; and to identify the contextual factors that influence knowledge dynamics in the TIS. These objectives are investigated using social network analysis based on bibliometric data (scientific publications and patents), keyword networks, a review of institutions, and a set of case studies where the primary data source are interviews with actors. Actors producing knowledge were from the university, healthcare, industry and science council sectors, although science councils played a small role. International actors were shown to bring new ideas into the TIS. The networks were fragmented, illustrating that knowledge diffusion through the networks was limited. This was especially the case in the patent networks as many actors patent in isolation. The keyword networks highlighted unrealised collaboration potential between actors based on their common research interests. The case studies revealed features of cross-sector interaction for orthopaedic device development not evident from network analysis based on bibliometric data. Drivers of knowledge development and knowledge diffusion were: inter-sectoral collaboration; the availability of resources; the affordability of available devices; and the positive externalities of allied TISs. The main barrier to knowledge development and diffusion was in the form of barriers to intersectoral collaboration. These include unmatched expectations from partners in collaboration, different views on intellectual property ownership, and burdensome university administrative processes. The orthopaedic devices TIS was structurally coupled to the embedded TIS and sectoral contexts, and externally linked and structurally coupled to its political context. Knowledge development and diffusion was found to be positively enhanced by innovation in the additive manufacturing TIS, with shared structural elements and resources. Knowledge development and diffusion was influenced by sectoral dynamics of the university, healthcare and industry sectors. This thesis makes the following contributions. First, it applies the TIS framework to a new focus area, namely medical device development, in a developing country context. Second, it makes two unique methodological contributions: it presents an index to capture the extent of sectoral collaboration in a network; and it develops a method for determining the collaboration potential of actors in a network based on cognitive distance

Social dynamics, network structure, and information diffusion in fish shoals.

Animal populations are often highly structured, with individuals differing in terms of whom they interact with and how frequently they do so. The resulting pattern of relationships constitutes a population’s social network. In this dissertation, I examine how environmental variation can shape social networks and influence information flow within them. In Chapter I, I review the history of social network analysis in animal behavior research, and discuss recent insights generated by network approaches in behavioral ecology. I focus on the fields of: social learning, collective behavior, animal personalities, and cooperation. Animal network studies are often criticized for a lack of replication at the network level and an over-reliance on descriptive approaches in lieu of hypothesis testing. Small, shoaling fish may provide a means to address these concerns, as manipulative experiments can be conducted on replicate social groups under captive conditions. Chapters III–V examine the impacts of environmental variation on the social networks of Trinidadian guppy (Poecilia reticulata) shoals, the social dynamics from which they emerge, and information diffusion within them. In the experiments described in Chapter III, I manipulated shoal composition in terms of within-group familiarity. Mixed shoals of familiar and unfamiliar fish exhibited greater homogeneity in network structure relative to other groups, which likely contributed to the rapid diffusion of foraging information observed within them. In the experiments discussed in Chapter IV, I manipulated the within-shoal mixture of personality types. In addition to impacting frequencies of partner switching and patterns of phenotypic assortment, individual- and group-level personality variation had strong effects on the initial acquisition of novel foraging information and the speed of its transmission through a group. In the experiments in Chapter V, I manipulated the ambient predation risk perceived by groups. High-risk conditions were associated with shifts in network structure consistent with attempts to minimize predation risk. High ambient risk also impeded the acquisition and subsequent transmission of foraging information, likely due to heightened neophobia and/or an increase in the perceived costs of personal sampling. I conclude in Chapter VI by considering the broader implications of my work and highlighting promising avenues for future research

Host-linked soil viral ecology along a permafrost thaw gradient

Climate change threatens to release abundant carbon that is sequestered at high latitudes, but the constraints on microbial metabolisms that mediate the release of methane and carbon dioxide are poorly understood1,2,3,4,5,6,7. The role of viruses, which are known to affect microbial dynamics, metabolism and biogeochemistry in the oceans8,9,10, remains largely unexplored in soil. Here, we aimed to investigate how viruses influence microbial ecology and carbon metabolism in peatland soils along a permafrost thaw gradient in Sweden. We recovered 1,907 viral populations (genomes and large genome fragments) from 197 bulk soil and size-fractionated metagenomes, 58% of which were detected in metatranscriptomes and presumed to be active. In silico predictions linked 35% of the viruses to microbial host populations, highlighting likely viral predators of key carbon-cycling microorganisms, including methanogens and methanotrophs. Lineage-specific virus/host ratios varied, suggesting that viral infection dynamics may differentially impact microbial responses to a changing climate. Virus-encoded glycoside hydrolases, including an endomannanase with confirmed functional activity, indicated that viruses influence complex carbon degradation and that viral abundances were significant predictors of methane dynamics. These findings suggest that viruses may impact ecosystem function in climate-critical, terrestrial habitats and identify multiple potential viral contributions to soil carbon cycling

Networks of change: extending Alaska-based communication networks to meet the challenges of the anthropocene

Thesis (Ph.D.) University of Alaska Fairbanks, 2017The Anthropocene is a contested term. As I conceptualize it throughout this dissertation, the Anthropocene is defined by an increased coupling of social and environmental systems at the global scale such that the by-products of human processes dominate the global stratigraphic record. Additionally, I connect the term to a worldview that sees this increased coupling as an existential threat to humanity's ability to sustain life on the planet. Awareness that the planet-wide scale of this coupling is fundamentally a new element in earth history is implicit in both understandings. How individuals and communities are impacted by this change varies greatly depending on a host of locally specific cross-scale factors. The range of scales (physical and social) that must be negotiated to manage these impacts places novel demands on the communication networks that shape human agency. Concern for how these demands are being met, and whose interests are being served in doing so, are the primary motivation for my research. My work is grounded in the communication-oriented theoretical traditions of media ecology and the more recent social-ecological system conceptualizations promoted in the study of resilience. I combine these ideas through a mixed methodology of digital ethnography and social network analysis to explore the communication dynamics of four Alaska-based social-ecological systems. The first two examples capture communication networks that formed in response to singular, rapid change environmental events (a coastal storm and river flood). The latter two map communication networks that have formed in response to more diffuse, slower acting environmental changes (a regional webinar series and an international arctic change conference). In each example, individuals or organizations enter and exit the mapped network(s) as they engage in the issue and specific communication channel being observed. Under these parameters a cyclic pattern of network expansion and contraction is identified. Expansion events are heavily influenced by established relationships retained during previous contraction periods. Many organizational outreach efforts are focused on triggering and participating in expansion events, however my observations highlight the role of legacy networks in system change. I suggest that for organizations interested in fostering sustainable socialecological relationships in the Anthropocene, strategic intervention may best be accomplished through careful consideration of how communicative relationships are maintained immediately following and in between expansion events. In the final sections of my dissertation I present a process template to support organizations interested in doing so. I include a complete set of learning activities to facilitate organizational use as well as examples of how the Alaska Native Knowledge Network is currently applying the process to meet their unique organizational needs

QUANTITATIVE SOCIAL SCIENCE METHODS, SOCIAL NETWORKS, AND SCALAR MISMATCHES: ADVANCING SOCIAL-ECOLOGICAL SYSTEMS SCIENCE TOWARDS ADAPTATION AND TRANSFORMATION

The adaptive capacity of social-ecological systems to maintain resilience or undergo transformation is increasingly important for navigating global change. Although social interactions and ecological disturbances are often cited as an essential element of social-ecological systems, social interactions are often undertheorized and simplistic, and the relative effects of both social and ecological processes are rarely considered in tandem. In this dissertation, I work towards advancing social-ecological systems research by highlighting opportunities for improved quantitative social science methods, using structurally explicit methods to evaluate the mechanisms underpinning social interactions, and characterizing scalar mismatches in a social-ecological system experiencing a regime shift. In Chapter 1, I provide an overview and introduction for my dissertation. In Chapter 2, I undertook a literature review of social-ecological system studies that quantified social interactions, concluding with a typology for improving conceptual clarity, a compendium of social interaction measures including mapped empirical relationships of each to focal concepts in social-ecological systems science to support theoretical development, and a discussion of opportunities for improved treatment of social interaction complexity in future studies. In Chapter 3, I assessed how social networks and disturbance influenced behaviors of agricultural producers navigating a wide-spread regime shift in the Great Plains biome of Nebraska, US. This social-ecological system is experiencing a regime shift, whereby eastern redcedar is encroaching upon grasslands causing persistent change. I found social network measures were not only more predictive of management behavior than disturbance, but also more predictive of transformative, rather than adaptive, behavior. These findings indicate social interactions, though often overlooked, are critical for influencing adaptive and transformative behavior in social-ecological systems. In Chapter 4, I characterized scalar mismatches between social and ecological components of the Great Plains biome in Nebraska. I found that individual producers respond to collective-level factors and regional-level disturbance as they attempt to manage this regime shift, often with limited success, indicating that the social level responsible for managing this transition is misaligned with the ecological level of the process. These findings highlight opportunities for higher social levels to support individual-level efforts to manage regime shifts in this social-ecological system in Nebraska with implications for detecting and characterizing scalar mismatches globally. In Chapter 5, I synthesize my findings and provide an arc of my contribution to social-ecological systems system

In the loop: a social network approach to the willingness to communicate in the L2 (L2 WTC)

Despite the conceptual importance of investigating the social context(s) in which second-language (L2) learning and use take place, the decade-old “social turn” within the field of second-language acquisition (SLA) has yet to produce a “parsimonious system of valid and generalizable parameters to describe contextual characteristics” (Dörnyei, 2009a, p. 238). Accordingly, investigating social network structure has recently been suggested as a general approach to examining the link between person and environment (Beckner, et al., 2009). In the current thesis, I offer a network approach in which second-language (L2) learning and use is regarded both as purposeful and as constrained by one’s social relationships. Subsequently, in a first-of-its-kind study within SLA, I apply social network analysis – a diverse array of formally-defined measures of social position and other socio-structural features – to conceptualize and empirically test the relationship between social structure and the willingness to communicate in the L2 (L2 WTC), defined as the “readiness to enter into discourse at a particular time with a specific person or persons, using a L2” (MacIntyre, et al., 1998, p. 547). In a study of Chinese-speaking international students at a British university, trait-like L2 WTC is found to predict cross-cultural adjustment, suggesting the role of actively engaging with one’s new cultural surroundings in establishing an adaptive person-environment fit. Subsequently, in the first study to apply modern, graph-theoretic notions of social position to a network of L2 learners, a significant relationship is found between various notions of structural position among a network of international English-for-Academic-Purposes students, and dispositional L2 WTC. Overall, the results support L2 WTC as both purposeful and constrained, learned from one’s past interactions, yet pushing the individual to take advantage of opportunities to communicate in the L2. Implications, limitations, and future directions of a social network approach to L2 learning and use are also discussed

Structure and dynamics of core-periphery networks

Recent studies uncovered important core/periphery network structures characterizing complex sets of cooperative and competitive interactions between network nodes, be they proteins, cells, species or humans. Better characterization of the structure, dynamics and function of core/periphery networks is a key step of our understanding cellular functions, species adaptation, social and market changes. Here we summarize the current knowledge of the structure and dynamics of "traditional" core/periphery networks, rich-clubs, nested, bow-tie and onion networks. Comparing core/periphery structures with network modules, we discriminate between global and local cores. The core/periphery network organization lies in the middle of several extreme properties, such as random/condensed structures, clique/star configurations, network symmetry/asymmetry, network assortativity/disassortativity, as well as network hierarchy/anti-hierarchy. These properties of high complexity together with the large degeneracy of core pathways ensuring cooperation and providing multiple options of network flow re-channelling greatly contribute to the high robustness of complex systems. Core processes enable a coordinated response to various stimuli, decrease noise, and evolve slowly. The integrative function of network cores is an important step in the development of a large variety of complex organisms and organizations. In addition to these important features and several decades of research interest, studies on core/periphery networks still have a number of unexplored areas.Comment: a comprehensive review of 41 pages, 2 figures, 1 table and 182 reference