Overview of complex systems in sport

The complex systems approach offers an opportunity to replace the extant pre-dominant mechanistic view on sport-related phenomena. The emphasis on the environment-system relationship, the applications of complexity principles, and the use of nonlinear dynamics mathematical tools propose a deep change in sport science. Coordination dynamics, ecological dynamics, and network approaches have been successfully applied to the study of different sport-related behaviors, from movement patterns that emerge at different scales constrained by specific sport contexts to game dynamics. Sport benefit from the use of such approaches in the understanding of technical, tactical, or physical conditioning aspects which change their meaning and dilute their frontiers. The creation of new learning and training strategies for teams and individual athletes is a main practical consequence. Some challenges for the future are investigating the influence of key control parameters in the nonlinear behavior of athlete-environment systems and the possible relatedness of the dynamics and constraints acting at different spatio-temporal scales in team sports. Modelling sport-related phenomena can make useful contributions to a better understanding of complex systems and vice-versa.

Capturing complex, non-linear team behaviours during competitive football performance

This study investigated changes in the complexity (magnitude and structure of variability) of the collective behaviours of association football teams during competitive performance. Raw positional data from an entire competitive match between two professional teams were obtained with the ProZone® tracking system. Five compound positional variables were used to investigate the collective patterns of performance of each team including: surface area, stretch index, team length, team width, and geometrical centre. Analyses involve the coefficient of variation (%CV) and approximate entropy (ApEn), as well as the linear association between both parameters. Collective measures successfully captured the idiosyncratic behaviours of each team and their variations across the six time periods of the match. Key events such as goals scored and game breaks (such as half time and full time) seemed to influence the collective patterns of performance. While ApEn values significantly decreased during each half, the %CV increased. Teams seem to become more regular and predictable, but with increased magnitudes of variation in their organisational shape over the natural course of a match.

Specification & design of safety technologies for complex socio-technical systems : low-cost level crossings case study

The introduction of safety technologies into complex socio-technical systems requires an integrated and holistic approach to HF and engineering, considering the effects of failures not only within system boundaries, but also at the interfaces with other systems and humans. Level crossing warning devices are examples of such systems where technically safe states within the system boundary can influence road user performance, giving rise to other hazards that degrade safety of the system. Chris will discuss the challenges that have been encountered to date in developing a safety argument in support of low-cost level crossing warning devices. The design and failure modes of level crossing warning devices are known to have a significant influence on road user performance; however, quantifying this effect is one of the ongoing challenges in determining appropriate reliability and availability targets for low-cost level crossing warning devices.

Scepticism and trust: two counterpoint essentials in science education for complex socio-scientific issues

In this response to Tom G. K. Bryce and Stephen P. Day’s (Cult Stud Sci Educ. doi:10.1007/s11422-013-9500-0, 2013) original article, I share with them their interest in the teaching of climate change in school science, but I widen it to include other contemporary complex socio-scientific issues that also need to be discussed. I use an alternative view of the relationship between science, technology and society, supported by evidence from both science and society, to suggest science-informed citizens as a more realistic outcome image of school science than the authors’ one of mini-scientists. The intellectual independence of students Bryce and Day assume, and intend for school science, is countered with an active intellectual dependence. It is only in relation to emerging and uncertain scientific contexts that students should be taught about scepticism, but they also need to learn when, and why to trust science as an antidote to the expressions of doubting it. Some suggestions for pedagogies that could lead to these new learnings are made. The very recent fifth report of the IPCC answers many of their concerns about climate change.

An Artificial Neutral Network (ANN) model for predicting biodiesel kinetic viscosity as a function of temperature and chemical compositions

An Artificial Neural Network (ANN) is a computational modeling tool which has found extensive acceptance in many disciplines for modeling complex real world problems. An ANN can model problems through learning by example, rather than by fully understanding the detailed characteristics and physics of the system. In the present study, the accuracy and predictive power of an ANN was evaluated in predicting kinetic viscosity of biodiesels over a wide range of temperatures typically encountered in diesel engine operation. In this model, temperature and chemical composition of biodiesel were used as input variables. In order to obtain the necessary data for model development, the chemical composition and temperature dependent fuel properties of ten different types of biodiesels were measured experimentally using laboratory standard testing equipments following internationally recognized testing procedures. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture was optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the absolute fraction of variance (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found that ANN is highly accurate in predicting the viscosity of biodiesel and demonstrates the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties at different temperature levels. Therefore the model developed in this study can be a useful tool in accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.

A randomized controlled trial of self-management programme improves health-related outcomes of older people with heart failure

Aims This paper is a report on the effectiveness of a self-management programme based on the self-efficacy construct, in older people with heart failure. Background Heart failure is a major health problem worldwide, with high mortality and morbidity, making it a leading cause of hospitalization. Heart failure is associated with a complex set of symptoms that arise from problems in fluid and sodium retention. Hence, managing salt and fluid intake is important and can be enhanced by improving patients' self-efficacy in changing their behaviour. Design Randomized controlled trial. Methods Heart failure patients attending cardiac clinics in northern Taiwan from October 2006–May 2007 were randomly assigned to two groups: control (n = 46) and intervention (n = 47). The intervention group received a 12-week self-management programme that emphasized self-monitoring of salt/fluid intake and heart failure-related symptoms. Data were collected at baseline as well as 4 and 12 weeks later. Data analysis to test the hypotheses used repeated-measures anova models. Results Participants who received the intervention programme had significantly better self-efficacy for salt and fluid control, self-management behaviour and their heart failure-related symptoms were significantly lower than participants in the control group. However, the two groups did not differ significantly in health service use. Conclusion The self-management programme improved self-efficacy for salt and fluid control, self-management behaviours, and decreased heart failure-related symptoms in older Taiwanese outpatients with heart failure. Nursing interventions to improve health-related outcomes for patients with heart failure should emphasize self-efficacy in the self-management of their disease.

Contact Lens Complications [Third Edition]

"Contact Lens Complications has become established as the definitive guide to the ocular response to contact lens wear. In this highly anticipated third edition, award-winning contact lens author, clinician and researcher, Professor Nathan Efron, presents a thoroughly revised and expanded, clinician-friendly account of how to identify, understand and manage contact lens complications in modern-day practice. Professor Efron is renowned for his ability to distil often complex principles of ocular physiology and pathology into an easy-to-read, highly structured format. The subject matter is systematically laid out, with various complications arranged logically by tissue structure - which is the way practitioners naturally approach clinical problems. Beautifully presented and lavishly illustrated with full-colour schematic diagrams and clinical pictures, this book can serve as both a practical chair-side manual and authoritative reference."--publisher website

'Explain in plain English' questions revisited : data structures problems

Recent studies have linked the ability of novice (CS1) programmers to read and explain code with their ability to write code. This study extends earlier work by asking CS2 students to explain object-oriented data structures problems that involve recursion. Results show a strong correlation between ability to explain code at an abstract level and performance on code writing and code reading test problems for these object-oriented data structures problems. The authors postulate that there is a common set of skills concerned with reasoning about programs that explains the correlation between writing code and explaining code. The authors suggest that an overly exclusive emphasis on code writing may be detrimental to learning to program. Non-code writing learning activities (e.g., reading and explaining code) are likely to improve student ability to reason about code and, by extension, improve student ability to write code. A judicious mix of code-writing and code-reading activities is recommended.

On the use of complex numbers in quantum models for information retrieval

Quantum-inspired models have recently attracted increasing attention in Information Retrieval. An intriguing characteristic of the mathematical framework of quantum theory is the presence of complex numbers. However, it is unclear what such numbers could or would actually represent or mean in Information Retrieval. The goal of this paper is to discuss the role of complex numbers within the context of Information Retrieval. First, we introduce how complex numbers are used in quantum probability theory. Then, we examine van Rijsbergen’s proposal of evoking complex valued representations of informations objects. We empirically show that such a representation is unlikely to be effective in practice (confuting its usefulness in Information Retrieval). We then explore alternative proposals which may be more successful at realising the power of complex numbers.

Document ranking with quantum probabilities

In this thesis we investigate the use of quantum probability theory for ranking documents. Quantum probability theory is used to estimate the probability of relevance of a document given a user's query. We posit that quantum probability theory can lead to a better estimation of the probability of a document being relevant to a user's query than the common approach, i. e. the Probability Ranking Principle (PRP), which is based upon Kolmogorovian probability theory. Following our hypothesis, we formulate an analogy between the document retrieval scenario and a physical scenario, that of the double slit experiment. Through the analogy, we propose a novel ranking approach, the quantum probability ranking principle (qPRP). Key to our proposal is the presence of quantum interference. Mathematically, this is the statistical deviation between empirical observations and expected values predicted by the Kolmogorovian rule of additivity of probabilities of disjoint events in configurations such that of the double slit experiment. We propose an interpretation of quantum interference in the document ranking scenario, and examine how quantum interference can be effectively estimated for document retrieval. To validate our proposal and to gain more insights about approaches for document ranking, we (1) analyse PRP, qPRP and other ranking approaches, exposing the assumptions underlying their ranking criteria and formulating the conditions for the optimality of the two ranking principles, (2) empirically compare three ranking principles (i. e. PRP, interactive PRP, and qPRP) and two state-of-the-art ranking strategies in two retrieval scenarios, those of ad-hoc retrieval and diversity retrieval, (3) analytically contrast the ranking criteria of the examined approaches, exposing similarities and differences, (4) study the ranking behaviours of approaches alternative to PRP in terms of the kinematics they impose on relevant documents, i. e. by considering the extent and direction of the movements of relevant documents across the ranking recorded when comparing PRP against its alternatives. Our findings show that the effectiveness of the examined ranking approaches strongly depends upon the evaluation context. In the traditional evaluation context of ad-hoc retrieval, PRP is empirically shown to be better or comparable to alternative ranking approaches. However, when we turn to examine evaluation contexts that account for interdependent document relevance (i. e. when the relevance of a document is assessed also with respect to other retrieved documents, as it is the case in the diversity retrieval scenario) then the use of quantum probability theory and thus of qPRP is shown to improve retrieval and ranking effectiveness over the traditional PRP and alternative ranking strategies, such as Maximal Marginal Relevance, Portfolio theory, and Interactive PRP. This work represents a significant step forward regarding the use of quantum theory in information retrieval. It demonstrates in fact that the application of quantum theory to problems within information retrieval can lead to improvements both in modelling power and retrieval effectiveness, allowing the constructions of models that capture the complexity of information retrieval situations. Furthermore, the thesis opens up a number of lines for future research. These include: (1) investigating estimations and approximations of quantum interference in qPRP; (2) exploiting complex numbers for the representation of documents and queries, and; (3) applying the concepts underlying qPRP to tasks other than document ranking.

Combining word semantics within complex Hilbert space for information retrieval

Complex numbers are a fundamental aspect of the mathematical formalism of quantum physics. Quantum-like models developed outside physics often overlooked the role of complex numbers. Specifically, previous models in Information Retrieval (IR) ignored complex numbers. We argue that to advance the use of quantum models of IR, one has to lift the constraint of real-valued representations of the information space, and package more information within the representation by means of complex numbers. As a first attempt, we propose a complex-valued representation for IR, which explicitly uses complex valued Hilbert spaces, and thus where terms, documents and queries are represented as complex-valued vectors. The proposal consists of integrating distributional semantics evidence within the real component of a term vector; whereas, ontological information is encoded in the imaginary component. Our proposal has the merit of lifting the role of complex numbers from a computational byproduct of the model to the very mathematical texture that unifies different levels of semantic information. An empirical instantiation of our proposal is tested in the TREC Medical Record task of retrieving cohorts for clinical studies.

Differentiation of complex lipid isomers by radical-directed dissociation mass spectrometry

Contemporary lipidomics protocols are dependent on conventional tandem mass spectrometry for lipid identification. This approach is extremely powerful for determining lipid class and identifying the number of carbons and the degree of unsaturation of any acyl-chain substituents. Such analyses are however, blind to isomeric variants arising from different carbon carbon bonding motifs within these chains including double bond position, chain branching, and cyclic structures. This limitation arises from the fact that conventional, low energy collision-induced dissociation of even-electron lipid ions does not give rise to product ions from intrachain fragmentation of the fatty acyl moieties. To overcome this limitation, we have applied radical-directed dissociation (RDD) to the study of lipids for the first time. In this approach, bifunctional molecules that contain a photocaged radical initiator and a lipid-adducting group, such as 4-iodoaniline and 4-iodobenzoic acid, are used to form noncovalent complexes (i.e., adduct ions) with a lipid during electrospray ionization. Laser irradiation of these complexes at UV wavelengths (266 nm) cleaves the carbon iodine bond to liberate a highly reactive phenyl radical. Subsequent activation of the nascent radical ions results in RDD with significant intrachain fragmentation of acyl moieties. This approach provides diagnostic fragments that are associated with the double bond position and the positions of chain branching in glycerophospholipids, sphingomyelins and triacylglycerols and thus can be used to differentiate isomeric lipids differing only in such motifs. RDD is demonstrated for well-defined lipid standards and also reveals lipid structural diversity in olive oil and human very-low density lipoprotein.

A sub‒domain smoothed Galerkin method for solid mechanics problems

A sub‒domain smoothed Galerkin method is proposed to integrate the advantages of mesh‒free Galerkin method and FEM. Arbitrarily shaped sub‒domains are predefined in problems domain with mesh‒free nodes. In each sub‒domain, based on mesh‒free Galerkin weak formulation, the local discrete equation can be obtained by using the moving Kriging interpolation, which is similar to the discretization of the high‒order finite elements. Strain smoothing technique is subsequently applied to the nodal integration of sub‒domain by dividing the sub‒domain into several smoothing cells. Moreover, condensation of DOF can also be introduced into the local discrete equations to improve the computational efficiency. The global governing equations of present method are obtained on the basis of the scheme of FEM by assembling all local discrete equations of the sub‒domains. The mesh‒free properties of Galerkin method are retained in each sub‒domain. Several 2D elastic problems have been solved on the basis of this newly proposed method to validate its computational performance. These numerical examples proved that the newly proposed sub‒domain smoothed Galerkin method is a robust technique to solve solid mechanics problems based on its characteristics of high computational efficiency, good accuracy, and convergence.

Evolving a design driven ‘hybrid’ research approach to inform and advance sustainable outcomes in the built environment sector

A significant reduction in global greenhouse gas (GHG) emissions is a priority, and the preservation of existing building stock presents a significant opportunity to reduce the carbon footprint of our built environment. Within this ‘wicked’ problem context, and moving beyond the ad hoc and incremental performance improvements that have been made to date, collaborative and multidisciplinary efforts are required to find rapid and transformational solutions. Design has emerged as a strategic and redirective practice, and lessons can therefore be learned about transformation and potentially applied in the built environment. The purpose of this paper is to discuss a pragmatic and novel research approach for undertaking such applied design driven research. This paper begins with a discussion of key contributions from design science (rational) and action research (reflective) philosophies in creating an emerging methodological ‘hybrid design approach’. This research approach is then discussed in relation to its application to specific research exploring the processes, methods and lessons from design in heritage building retrofit projects. Drawing on both industry and academic knowledge to ensure relevance and rigour, it is anticipated that the hybrid design approach will be useful for others tackling such complex wicked problems that require context-specific solutions.

Hybrid genetic algorithm for elimination of severe stress concentration in railhead ends

This paper presents a computational method for eliminating severe stress concentration at the unsupported railhead ends in rail joints through innovative shape optimization of the contact zone, which is complex due to near field nonlinear contact. With a view to minimizing the computational efforts, hybrid genetic algorithm method coupled with parametric finite element has been developed and compared with the traditional genetic algorithm (GA). The shape of railhead top surface where the wheel contacts nonlinearly was optimized using the hybridized GA method. Comparative study of the optimal result and the search efficiency between the traditional and hybrid GA methods has shown that the hybridized GA provides the optimal shape in fewer computational cycles without losing accuracy. The method will be beneficial to solving complex engineering problems involving contact nonlinearity.