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Drawing on critical realism, complexity theory, and emergence, this chapter supports the call to re-imagine doctoral writing by arguing that academic writing in general is a complex open and emergent social system that can change. Several reasons to re-imagine doctoral writing are discussed. The first reason is that academic writings already exhibit considerable diversity. This suggests that the conditions of possibility for re-imagining them are already in place and provide a conceptual space from which to further imagine. Second, there are\ud epistemic reasons for re-thinking how we write, as evidenced by research on socio-semiotics. Several examples of doctoral writers\ud who have re-imagined their writing for epistemic reasons are given. To explain how change in social phenomena is possible and how it can continue to be justified, I draw on the theory of complex permeable open systems. These systems are emergent and, as such, allow us to think of social phenomena, such as writing, as non-reductive organic unities whose characteristics emerge from but cannot be reduced to any single constituent feature (such as grammar or lexis). By re-thinking academic writings in this way, we can provide a rationale to explain how they can continue to change. The chapter concludes by sharing the work of scholars engaged in re-imagining doctoral writings. The significance for writing studies is that critical realism offers a systematic and critical space within which to explain change\ud in social phenomena and provides a theoretical foundation for continuing to re-imagine conditions of possibility.

The large number of Web pages on many Web sites has raised\ud navigational problems. Markov chains have recently been used to model user navigational behavior on the World Wide Web (WWW). In this paper, we propose a method for constructing a Markov model of a Web site based on past\ud visitor behavior. We use the Markov model to make link predictions that assist new users to navigate the Web site. An algorithm for transition probability\ud matrix compression has been used to cluster Web pages with similar transition behaviors and compress the transition matrix to an optimal size for efficient probability calculation in link prediction. A maximal forward path method is used to further improve the efficiency of link prediction. Link prediction has been implemented in an online system called ONE (Online Navigation Explorer) to assist users' navigation in the adaptive Web site.

Since the advent of New Austrian Tunneling Method (NATM), shotcrete as a primary means of support in tunnels has been widely applied. It’s most important features are durability, speed of application and cost effectiveness. This paper introduces some tables that provide guidelines for the thickness of shotcrete required in some common situations of mine roadways. In order to devise such tables, two different arch sections, together with three different overburden types, were considered. Geotechnical parameters such as apparent cohesion and angle of internal friction of surrounding rocks were chosen, based on the five-category classification of Bieniawski. Two K0 factors (the ratio of horizontal stress to vertical stress) and an average rock density were utilized. Using numerical methods, 60 models were then devised in this way. By applying interaction diagrams of axial force and the bending moment for different thicknesses of shotcrete, appropriate shotcrete thickness for these models were calculated. The results of this research, as well as the methodology applied, can be used in mining roadway support design and all types of civil engineering tunnels.

Within the context of the European Commission’s recent policy gaze on teacher education (European Commission, Improving teacher quality: The EU agenda – lifelong learning: policies and programme. Brussels, April 2010, EAC.B.2. D (2010) PSH, 2010; European Commission, Supporting teacher educators for better learning outcomes. European Commission, Brussels, 2013; European Commission, Strengthening teaching in Europe: new evidence from teachers compiled by Eurydice and CRELL, June 2015. Available from: http://ec.europa.eu/education/library/policy/teaching-profession-practices_en.pdf, 2015), this chapter contributes to an improved understanding of the hybrid, poly-contextualised identities of school-based teacher educators. At a time of systemic change in the education systems of many countries, teachers in schools are increasingly being asked to be responsible for the education and training of future teachers. Within the English backdrop of a rapidly changing landscape for teacher education, we present initial findings from a small-scale study exploring, through interview data, how the knowledge bases and identities of two groups of insiders, university and school-based teacher educators, were perceived by those hybrid teacher educators (Zeichner 2010) working in schools. Our findings reveal differences in school-based teacher educators’ views on their work and the work of university-based teacher educators, school-based teacher educators’ views on the role educational research has in the work they do and the ways in which different professional pathways (e.g. occupational/university; primary/secondary) influence views on what it means to be a teacher educator.

The Multilayer Perceptron (MLP) is a neural network architecture that is widely used for regression, classification and time series forecasting. One often cited disadvantage of the MLP, however, is the difficulty associated with human understanding of a particular MLP’s function. This so called black box limitation is due to the fact that the weights of the network reveal little about structure of the function they implement. This paper proposes a method for understanding the structure of the function learned by MLPs that model functions of the class \(f:\{-1,1\}^n \rightarrow \mathbb {R}^m\). This includes regression and classification models. A Walsh decomposition of the function implemented by a trained MLP is performed and the coefficients analysed. The advantage of a Walsh decomposition is that it explicitly separates the contribution to the function made by each subset of input neurons. It also allows networks to be compared in terms of their structure and complexity. The method is demonstrated on some small toy functions and on the larger problem of the MNIST handwritten digit classification data set.

Martian gullies were initially hypothesized to be carved by liquid water, due to their resemblance to gullies on Earth. Recent observations have highlighted significant sediment transport events occurring in Martian gullies at times and places where CO2 ice should be actively sublimating. Here we explore the role of CO2 sublimation in mobilizing sediment through laboratory simulation. In our previous experimental work, we reported the first observations of sediment slope movement triggered by the sublimation of CO2 frost. We used a Mars regolith simulant near the angle of repose. The current study extends our previous work by including two additional substrates, fine and coarse sand, and by testing slope angles down to 10°. We find that the Mars regolith simulant is active down to 17°, the fine sand is active only near the angle of repose and the coarse sand shows negligible movement. Using an analytical model, we show that under Martian gravity motion should be possible at even lower slope angles. We conclude that these mass-wasting processes could be involved in shaping Martian gullies at the present day and intriguingly the newly reported CO2-creep process could provide an alternative explanation for putative solifluction lobes on Mars.

Part 12: Workshops; International audience; The manipulation of information and the dissemination of “fake news” are practices that trace back to the early records of human history. Significant changes in the technological environment enabling ubiquity, immediacy and considerable anonymity, have facilitated the spreading of misinformation in unforeseen ways, raising concerns around people’s (mis)perception of social issues worldwide. As a wicked problem, limiting the harm caused by misinformation goes beyond technical solutions, requiring also regulatory and behavioural changes. This workshop proposes to unpack the challenge at hand by bringing together diverse perspectives to the problem. Based on participatory design principles, it will challenge participants to critically reflect the limits of existing socio-technical approaches and co-create scenarios in which digital platforms support misinformation resilience.

Abstract This chapter deals with the processes by which the European vernaculars gained prestige vis-à-vis Latin from the late Middle Ages onwards. It addresses the “idea” of a standard language and how this has been advanced by particular actors and institutions across Europe, focusing primarily on the period from the Renaissance to the eighteenth century. It also considers whether standard languages are now outmoded concepts and suggests that we are now in a period characterized by destandardization.

User evaluations of search engines are expensive and not easy to replicate. The problem is even more pronounced when assessing adaptive search systems, for example system-generated query modification suggestions that can be derived from past user interactions with a search engine. Automatically predicting the performance of different modification suggestion models before getting the users involved is therefore highly desirable. AutoEval is an evaluation methodology that assesses the quality of query modifications generated by a model using the query logs of past user interactions with the system. We present experimental results of applying this methodology to different adaptive algorithms which suggest that the predicted quality of different algorithms is in line with user assessments. This makes AutoEval a suitable evaluation framework for adaptive interactive search engines.

Key feature of a context-aware application is the ability to adapt based on the change of context. Two approaches that are widely used in this regard are the context-action pair mapping where developers match an action to execute for a particular context change and the adaptive learning where a context-aware application refines its action over time based on the preceding action’s outcome. Both these approaches have limitation which makes them unsuitable in situations where a context-aware application has to deal with unknown context changes. In this paper we propose a framework where adaptation is carried out via concurrent multi-action evaluation of a dynamically created action space. This dynamic creation of the action space eliminates the need for relying on the developers to create context-action pairs and the concurrent multi-action evaluation reduces the adaptation time as opposed to the iterative approach used by adaptive learning techniques. Using our reference implementation of the framework we show how it could be used to dynamically determine the threshold price in an e-commerce system which uses the name-your-own-price (NYOP) strategy.