Dual-phase evolution in complex adaptive systems

Paperin, Gregory; Green, David G.; Sadedin, Suzanne

doi:10.1098/rsif.2010.0719

Cited by 52 publications

(40 citation statements)

References 158 publications

(229 reference statements)

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“…However, some growing complex networks in the real world may not follow the consistence growing algorithm in evolution process [27]. According to a study on collaborations between scientists, small groups of scientists rely on few strong connections, while large groups show a high turnover of the members [26].…”

Section: Model and Methodsmentioning

confidence: 99%

Characteristics of a preferentially-attached network grown from a small world

Lee

2015

Journal of the Korean Physical Society

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We introduce a model for a preferentially attached network which has grown from a small world network. Here, the average path length and the clustering coefficient are estimated, and the topological properties of modeled networks are compared as the initial conditions are changed.As a result, it is shown that the topological properties of the initial network remain even after the network growth. However, the vulnerability of each to preferentially attached nodes being added is not the same. It is found that the average path length rapidly decreases as the ratio of preferentially attached nodes increases and that the characteristics of the initial network can be easily disappeared. On the other hand, the clustering coefficient of the initial network slowly decreases with the ratio of preferentially attached nodes and its clustering characteristic remains much longer.

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Section: Model and Methodsmentioning

confidence: 99%

Characteristics of a preferentially-attached network grown from a small world

Lee

2015

Journal of the Korean Physical Society

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“…A phase transition is a profound structural re-organisation when there is a large change in resource availability for maintenance. Sudden, rapid-acceleration phase transitions are associated with emergence, mutations, breakthroughs and development of autocatalytic systems which change the status quo and result in new situations which may improve fitness and survival (de Rosnay 2000).The study of such threshold dynamics gives interesting insights into plausible mechanisms for artificial manipulation of the process (Paperin et al 2011). Kiss et al (2009) suggest that in order for a phase transition to take place it is necessary to have increased complexity and increased exposure to new challenges and a reduction in available resources.…”

Section: The Role Of Phase Transitionmentioning

confidence: 99%

Reversal of Informational Entropy and the Acquisition of Germ-like Immortality by Somatic Cells

Kyriazis¹

2014

CAS

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We live within an increasingly technological, information-laden environment for the first time in human evolution. This subjects us (and will continue to subject us in an accelerating fashion) to an unremitting exposure to 'meaningful information that requires action'. Directly dependent upon this new environment are novel evolutionary pressures, which can modify existing resource allocation mechanisms and may eventually favour the survival of somatic cells (particularly neurons) at the expense of germ line cells. In this theoretical paper I argue that persistent, structured information-sharing in both virtual and real domains, leads to increased biological complexity and functionality, which reflects upon human survival characteristics. Certain biological immortalisation mechanisms currently employed by germ cells may thus need to be downgraded in order to enable somatic cells to manage these new energy demands placed by our modern environment. Relevant concepts from a variety of disciplines such as the evolution of complex adaptive systems, information theory, digital hyper-connectivity, and cell immortalisation will be reviewed. Using logical, though sometimes speculative arguments, I will attempt to describe a new biology. A biology not driven by sex and reproduction but by information and somatic longevity.

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“…Nursing homes are complex adaptive systems because they are comprised of a collection of individual agents (staff, residents, and families) with the freedom to act in ways that are not always totally predictable, and whose actions are interconnected; for example, one agent's actions change the context for other agents in the system [8]. Complexity science, the study of relationships between and among system agents and how they give rise to collective behaviors and outcomes [9], provides insight as to how these systems work. Key characteristics of complex adaptive systems are more fully defined in Table 1.…”

Section: Introductionmentioning

confidence: 99%

Tool for evaluating research implementation challenges: A sense-making protocol for addressing implementation challenges in complex research settings

et al. 2013

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BackgroundMany challenges arise in complex organizational interventions that threaten research integrity. This article describes a Tool for Evaluating Research Implementation Challenges (TECH), developed using a complexity science framework to assist research teams in assessing and managing these challenges.MethodsDuring the implementation of a multi-site, randomized controlled trial (RCT) of organizational interventions to reduce resident falls in eight nursing homes, we inductively developed, and later codified the TECH. The TECH was developed through processes that emerged from interactions among research team members and nursing home staff participants, including a purposive use of complexity science principles.ResultsThe TECH provided a structure to assess challenges systematically, consider their potential impact on intervention feasibility and fidelity, and determine actions to take. We codified the process into an algorithm that can be adopted or adapted for other research projects. We present selected examples of the use of the TECH that are relevant to many complex interventions.ConclusionsComplexity theory provides a useful lens through which research procedures can be developed to address implementation challenges that emerge from complex organizations and research designs. Sense-making is a group process in which diverse members interpret challenges when available information is ambiguous; the groups’ interpretations provide cues for taking action. Sense-making facilitates the creation of safe environments for generating innovative solutions that balance research integrity and practical issues. The challenges encountered during implementation of complex interventions are often unpredictable; however, adoption of a systematic process will allow investigators to address them in a consistent yet flexible manner, protecting fidelity. Research integrity is also protected by allowing for appropriate adaptations to intervention protocols that preserve the feasibility of ‘real world’ interventions.

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Dual-phase evolution in complex adaptive systems

Cited by 52 publications

References 158 publications

Characteristics of a preferentially-attached network grown from a small world

Characteristics of a preferentially-attached network grown from a small world

Reversal of Informational Entropy and the Acquisition of Germ-like Immortality by Somatic Cells

Tool for evaluating research implementation challenges: A sense-making protocol for addressing implementation challenges in complex research settings

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