Applying complexity science to air traffic management

Complexity science is the multidisciplinary study of complex systems. Its marked network orientation lends itself well to transport contexts. Key features of complexity science are introduced and defined, with a specific focus on the application to air traffic management. An overview of complex network theory is presented, with examples of its corresponding metrics and multiple scales. Complexity science is starting to make important contributions to performance assessment and system design: selected, applied air traffic management case studies are explored. The important contexts of uncertainty, resilience and emergent behaviour are discussed, with future research priorities summarised.

Application of computer-aided tomography techniques to visualize kelp holdfast structure reveals the importance of habitat complexity for supporting marine biodiversity

Ecosystem engineers that increase habitat complexity are keystone species in marine systems, increasing shelter and niche availability, and therefore biodiversity. For example, kelp holdfasts form intricate structures and host the largest number of organisms in kelp ecosystems. However, methods that quantify 3D habitat complexity have only seldom been used in marine habitats, and never in kelp holdfast communities. This study investigated the role of kelp holdfasts (Laminaria hyperborea) in supporting benthic faunal biodiversity. Computer-aided tomography (CT-) scanning was used to quantify the three-dimensional geometrical complexity of holdfasts, including volume, surface area and surface fractal dimension (FD). Additionally, the number of haptera, number of haptera per unit of volume, and age of kelps were estimated. These measurements were compared to faunal biodiversity and community structure, using partial least-squares regression and multivariate ordination. Holdfast volume explained most of the variance observed in biodiversity indices, however all other complexity measures also strongly contributed to the variance observed. Multivariate ordinations further revealed that surface area and haptera per unit of volume accounted for the patterns observed in faunal community structure. Using 3D image analysis, this study makes a strong contribution to elucidate quantitative mechanisms underlying the observed relationship between biodiversity and habitat complexity. Furthermore, the potential of CT-scanning as an ecological tool is demonstrated, and a methodology for its use in future similar studies is established. Such spatially resolved imager analysis could help identify structurally complex areas as biodiversity hotspots, and may support the prioritization of areas for conservation.

Application of computer-aided tomography techniques to visualize kelp holdfast structure reveals the importance of habitat complexity for supporting marine biodiversity

Ecosystem engineers that increase habitat complexity are keystone species in marine systems, increasing shelter and niche availability, and therefore biodiversity. For example, kelp holdfasts form intricate structures and host the largest number of organisms in kelp ecosystems. However, methods that quantify 3D habitat complexity have only seldom been used in marine habitats, and never in kelp holdfast communities. This study investigated the role of kelp holdfasts (Laminaria hyperborea) in supporting benthic faunal biodiversity. Computer-aided tomography (CT-) scanning was used to quantify the three-dimensional geometrical complexity of holdfasts, including volume, surface area and surface fractal dimension (FD). Additionally, the number of haptera, number of haptera per unit of volume, and age of kelps were estimated. These measurements were compared to faunal biodiversity and community structure, using partial least-squares regression and multivariate ordination. Holdfast volume explained most of the variance observed in biodiversity indices, however all other complexity measures also strongly contributed to the variance observed. Multivariate ordinations further revealed that surface area and haptera per unit of volume accounted for the patterns observed in faunal community structure. Using 3D image analysis, this study makes a strong contribution to elucidate quantitative mechanisms underlying the observed relationship between biodiversity and habitat complexity. Furthermore, the potential of CT-scanning as an ecological tool is demonstrated, and a methodology for its use in future similar studies is established. Such spatially resolved imager analysis could help identify structurally complex areas as biodiversity hotspots, and may support the prioritization of areas for conservation.

Newcomer Integration in Online Knowledge Communities: Exploring the Role of Dialogic Textual Complexity

Using online knowledge communities (OKCs) as informal learning environments poses the question how likely these will integrate newcomers as peripheral participants. Previous research has identified surface characteristics of the OKC dialog as integrativity predictors. Yet, little is known about the role of dialogic textual complexity. This contribution proposes a comprehensive approach based on previously validated textual complexity indexes and applies it to predict OKC integrativity. The dialog analysis of N = 14 blogger communities with a total of 1937 participants identified three main components of textual complexity: dialog participation, structure and cohesion. From these, dialog cohesion was higher in integrative OKCs, thus significantly predicting OKC integrativity. This result adds to previous OKC research by uncovering the depth of OKC discourse. For educational practice, the study suggests a way of empowering learners by automatically assessing the integrativity of OKCs in which they may attempt to participate and access community knowledge.

Predicting Student Performance and Differences in Learning Styles based on Textual Complexity Indices applied on Blog and Microblog Posts

Social media tools are increasingly popular in Computer Supported Collaborative Learning and the analysis of students' contributions on these tools is an emerging research direction. Previous studies have mainly focused on examining quantitative behavior indicators on social media tools. In contrast, the approach proposed in this paper relies on the actual content analysis of each student's contributions in a learning environment. More specifically, in this study, textual complexity analysis is applied to investigate how student's writing style on social media tools can be used to predict their academic performance and their learning style. Multiple textual complexity indices are used for analyzing the blog and microblog posts of 27 students engaged in a project-based learning activity. The preliminary results of this pilot study are encouraging, with several indexes predictive of student grades and/or learning styles.

Classifying Rational G-Spectra for Finite G

We give a new proof that for a finite group G, the category of rational G-equivariant spectra is Quillen equivalent to the product of the model categories of chain complexes of modules over the rational group ring of the Weyl group of H in G, as H runs over the conjugacy classes of subgroups of G. Furthermore, the Quillen equivalences of our proof are all symmetric monoidal. Thus we can understand categories of algebras or modules over a ring spectrum in terms of the algebraic model.

The comparative effects of habitat complexity on faunal assemblages of northern temperate artificial and natural reefs

<p>Several north temperate marine species were recorded on subtidal hard-substratum reef sites selected to produce a gradient of structural complexity. The study employed an established scuba-based census method, the belt transect. The three types of reef examined, with a measured gradient of increasing structural complexity, were natural rocky reef, artificial reef constructed of solid concrete blocks, and artificial reef made of concrete blocks with voids. Surveys were undertaken monthly over a calendar year using randomly placed fixed rope transects. For a number of conspicuous species of fish and invertebrates, significant differences were found between the levels of habitat complexity and abundance. Overall abundance for many of the species examined was 2-3 times higher on the complex artificial habitats than on simple artificial or natural reef habitats. The enhanced habitat availability produced by the increased structural complexity delivered through specifically designed artificial reefs may have the potential to augment faunal abundance while promoting species diversity. </p>

A monoidal algebraic model for rational SO(2)-spectra

The category of rational SO(2)--equivariant spectra admits an algebraic model. That is, there is an abelian category A(SO(2)) whose derived category is equivalent to the homotopy category of rational$SO(2)--equivariant spectra. An important question is: does this algebraic model capture the smash product of spectra? The category A(SO(2)) is known as Greenlees' standard model, it is an abelian category that has no projective objects and is constructed from modules over a non--Noetherian ring. As a consequence, the standard techniques for constructing a monoidal model structure cannot be applied. In this paper a monoidal model structure on A(SO(2)) is constructed and the derived tensor product on the homotopy category is shown to be compatible with the smash product of spectra. The method used is related to techniques developed by the author in earlier joint work with Roitzheim. That work constructed a monoidal model structure on Franke's exotic model for the K_(p)--local stable homotopy category. A monoidal Quillen equivalence to a simpler monoidal model category that has explicit generating sets is also given. Having monoidal model structures on the two categories removes a serious obstruction to constructing a series of monoidal Quillen equivalences between the algebraic model and rational SO(2)--equivariant spectra.

Building public policy on shifting sands: the case of the National Asset Management Agency

Over the last thirty years, there has been an increased demand for better management of public sector organisations (PSOs). This requires that they are answerable for the inputs that they are given but also for what they achieve with these inputs (Hood 1991; Hood 1995). It is suggested that this will improve the management of the organisation through better planning and control, and the achievement of greater accountability (Smith 1995). However, such a rational approach with clear goals and the means to measure achievement can cause difficulties for many PSOs. These difficulties include the distinctive nature of the public sector due to the political environment within which the public sector manager operates (Stewart and Walsh 1992) and the fact that PSOs will have many stakeholders, each of whom will have their own specific objectives based on their own perspective (Boyle 1995). This can <br/>result in goal ambiguity which means that there is leeway in interpreting the results of the PSO. The National Asset Management Agency (NAMA) was set up to bring stability to the financial system by buying loans from the banks (which were in most cases, non-performing loans). The intention was to cleanse the banks of these loans so that they could return to their normal business of taking deposits and making loans. However, the legislation, also gave NAMA a wide range of other responsibilities including responsibility for facilitating credit in the economy and protecting the interests of taxpayers. In more recent times, NAMA has been given responsibility for building social housing. This wide-range of activities is a clear example of a PSO being given multiple goals which may conflict and is therefore likely to lead to goal ambiguity. This makes it very difficult to evaluate NAMA’s performance as they are attempting to meet numerous goals at the same time and also highlights the complexity of policy making in the public sector. The purpose of this paper is to examine how NAMA dealt with goal ambiguity. This will be done through a thematic analysis of its annual reports over the last five years. The paper’s will contribute to the ongoing debate about the evaluation of PSOs and the complex environment within which they operate which makes evaluation difficult as they are <br/>answerable to multiple stakeholders who have different objectives and different criteria for measuring success.

Learning to manage complexity through simulation: students' challenges and possible strategies

<p>Many have called for medical students to learn how to manage complexity in healthcare. This study examines the nuances of students' challenges in coping with a complex simulation learning activity, using concepts from complexity theory, and suggests strategies to help them better understand and manage complexity.Wearing video glasses, participants took part in a simulation ward-based exercise that incorporated characteristics of complexity. Video footage was used to elicit interviews, which were transcribed. Using complexity theory as a theoretical lens, an iterative approach was taken to identify the challenges that participants faced and possible coping strategies using both interview transcripts and video footage.Students' challenges in coping with clinical complexity included being: a) unprepared for 'diving in', b) caught in an escalating system, c) captured by the patient, and d) unable to assert boundaries of acceptable practice.Many characteristics of complexity can be recreated in a ward-based simulation learning activity, affording learners an embodied and immersive experience of these complexity challenges. Possible strategies for managing complexity themes include: a) taking time to size up the system, b) attuning to what emerges, c) reducing complexity, d) boundary practices, and e) working with uncertainty. This study signals pedagogical opportunities for recognizing and dealing with complexity.</p>

Irish Credit Unions: Differential Regulation based on Business Model Complexity

This study examines the business model complexity of Irish credit unions using a latent class approach to measure structural performance over the period 2002 to 2013. The latent class approach allows the endogenous identification of a multi-class framework for business models based on credit union specific characteristics. The analysis finds a three class system to be appropriate with the multi-class model dependent on three financial viability characteristics. This finding is consistent with the deliberations of the Irish Commission on Credit Unions (2012) which identified complexity and diversity in the business models of Irish credit unions and recommended that such complexity and diversity could not be accommodated within a one size fits all regulatory framework. The analysis also highlights that two of the classes are subject to diseconomies of scale. This may suggest credit unions would benefit from a reduction in scale or perhaps that there is an imbalance in the present change process. Finally, relative performance differences are identified for each class in terms of technical efficiency. This suggests that there is an opportunity for credit unions to improve their performance by using within-class best practice or alternatively by switching to another class.

Rational O(2)–Equivariant Spectra

The category of rational O(2)-equivariant cohomology theories has an algebraic model A(O(2)), as established by work of Greenlees. That is, there is an equivalence of categories between the homotopy category of rational O(2)-equivariant spectra and the derived category of the abelian model DA(O(2)). In this paper we lift this equivalence of homotopy categories to the level of Quillen equivalences of model categories. This Quillen equivalence is also compatible with the Adams short exact sequence of the algebraic model.