Food in the city : urban food movements and the (re)imagining of urban spaces

Ethical food movements are growing in number throughout Australia. Amongst these diverse movements are urban agriculture initiatives, which articulate a multitude of social and environmental values. Yet, despite the long history of production and exchange of food in urban areas, planners (and others) often overlook its significance. To assist in addressing this oversight, we take the case study of Melbourne to examine the ways in which participants in urban agriculture are re-imagining urban spaces and the future of agriculture and food systems in Australia. We demonstrate that urban food advocates' politics and practices both challenge and resist the enclosure of urban spaces. This creates new frontiers that transgress social, political, ecological and economic boundaries and edges. These transgressions or counter-enclosures articulate new visions for secure and just food systems and, in so doing, offer insights to assist planners in ensuring Australian cities support socially just and environmentally responsible food systems.

Autonomous multisensor calibration and closed-loop fusion for SLAM

The vast majority of current robot mapping and navigation systems require specific well-characterized sensors that may require human-supervised calibration and are applicable only in one type of environment. Furthermore, if a sensor degrades in performance, either through damage to itself or changes in environmental conditions, the effect on the mapping system is usually catastrophic. In contrast, the natural world presents robust, reasonably well-characterized solutions to these problems. Using simple movement behaviors and neural learning mechanisms, rats calibrate their sensors for mapping and navigation in an incredibly diverse range of environments and then go on to adapt to sensor damage and changes in the environment over the course of their lifetimes. In this paper, we introduce similar movement-based autonomous calibration techniques that calibrate place recognition and self-motion processes as well as methods for online multisensor weighting and fusion. We present calibration and mapping results from multiple robot platforms and multisensory configurations in an office building, university campus, and forest. With moderate assumptions and almost no prior knowledge of the robot, sensor suite, or environment, the methods enable the bio-inspired RatSLAM system to generate topologically correct maps in the majority of experiments.

A phase-locked-loop design for the smooth operation of a hybrid microgrid

A microgrid contains both distributed generators (DGs) and loads and can be viewed by a controllable load by utilities. The DGs can be either inertial synchronous generators or non-inertial converter interfaced. Moreover, some of them can come online or go offline in plug and play fashion. The combination of these various types of operation makes the microgrid control a challenging task, especially when the microgrid operates in an autonomous mode. In this paper, a new phase locked loop (PLL) algorithm is proposed for smooth synchronization of plug and play DGs. A frequency droop for power sharing is used and a pseudo inertia has been introduced to non-inertial DGs in order to match their response with inertial DGs. The proposed strategy is validated through PSCAD simulation studies.

Distribution state estimation based on particle swarm and doubly loop mutant optimization (DLM-PSO)

This paper presents a novel algorithm based on particle swarm optimization (PSO) to estimate the states of electric distribution networks. In order to improve the performance, accuracy, convergence speed, and eliminate the stagnation effect of original PSO, a secondary PSO loop and mutation algorithm as well as stretching function is proposed. For accounting uncertainties of loads in distribution networks, pseudo-measurements is modeled as loads with the realistic errors. Simulation results on 6-bus radial and 34-bus IEEE test distribution networks show that the distribution state estimation based on proposed DLM-PSO presents lower estimation error and standard deviation in comparison with algorithms such as WLS, GA, HBMO, and original PSO.

Digital Literacy and the Spaces of Academic Discourse

Digital literacy poses a particular challenge to the research-led university. Although these universities are often at the forefront of introducing digital literacy initiatives—such as e-learning platforms, technological infrastructure, and digital repositories—these applications of digital literacy tend to be more instrumental or functional than critical or creative. Certainly, this clash of cultures between the instrumental/functional and the critical/analytical is at the heart of debates over the uses of digital literacy in higher education. However, this simple equation of political forces with instrumentality and the corresponding equation of the university with a tradition of reflective thought that brings criticism to bear on instrumentality elide the fact that this conflict is more deeply rooted within the academy. This essay argues that, in fact, much of the resistance to critical uses of digital literacy comes from within the institution of the university itself. That is, the university is bound up in a scriptural economy that prioritises the printed word and that reinforces its power by way of a normative, political, and spatialised academic discourse. It is this print-based scriptural economy—in which this essay must acknowledge its own complicity—that a critical approach to digital literacy threatens to disrupt or lay bare.

Editorial : Loop

This time last year we proposed the theme of the 'loop' issue to the M/C collective because it sounded deeply cool, satisfying our poststructuralist posturings about reflexivity and representation, while also tapping into everyday cultural objects and practices. We expected that the 'loop' issue would generate some interesting and varied responses, and it did. We received submissions about music, visual art, language, child development, pop-cultural artefacts, mathematics and culture in general. These explorations of disparate fields seemed, however, to be tied together by a common thread: the concept of "generation" itself. Each article in the 'loop' issue describes a loop that does not simply repeat an original operation, but that through iteration creates new possibilities and new meanings...

Using performance-based evaluation to close the loop between biological and robotic navigation

In this paper we describe the benefits of a performance-based approach to modeling biological systems for use in robotics. Specifically, we describe the RatSLAM system, a computational model of the navigation processes thought to drive navigation in a part of the rodent brain called the hippocampus. Unlike typical computational modeling approaches, which focus on biological fidelity, RatSLAM’s development cycle has been driven primarily by performance evaluation on robots navigating in a wide variety of challenging, real world environments. We briefly describe three seminal results, two in robotics and one in biology. In addition, we present current research on brain-inspired learning algorithms with the aim of enabling a robot to autonomously learn how best to use its sensor suite to navigate, without requiring any specific knowledge of the robot, sensor types or environment characteristics. Our aim is to drive discussion on the merits of practical, performance-focused implementations of biological models in robotics.

Dilemmatic spaces : high-stakes testing and the possibilities of collaborative knowledge work to generate learning innovations

This paper examines collaborative researcher-practitioner knowledge work around assessment data in culturally diverse, low- socioeconomic school communities in Queensland, Australia. Specifically, the paper draws on interview accounts about the work of a bridging knowledge flows between a local university and a cluster of schools. We draw on Bernstein’s (2000) concept of recontextualisation to explore the processes of knowledge mediation in dialogues around student assessment data to design instructional innovations. We argue that critical policy studies need to explore the complex ways in which neoliberal education policies are enacted in local sites. Moreover, we suggest that an analysis of collaborative knowledge work designed to improve student learning outcomes in low-socioeconomic school communities necessitates attention to the principles regulating knowledge flows across boundaries. In addition, it necessitates attention to the ways in which mediators navigate dilemmatic spaces, anxieties and affects/feelings in order to generate innovative learning designs in the current global context of high-stakes national testing and accountability regimes.

Total energy shaping of a class of underactuated Port-Hamiltonian Systems using a new set of closed-loop potential shape variables

This paper proposes a method for designing set-point regulation controllers for a class of underactuated mechanical systems in Port-Hamiltonian System (PHS) form. A new set of potential shape variables in closed loop is proposed, which can replace the set of open loop shape variables-the configuration variables that appear in the kinetic energy. With this choice, the closed-loop potential energy contains free functions of the new variables. By expressing the regulation objective in terms of these new potential shape variables, the desired equilibrium can be assigned and there is freedom to reshape the potential energy to achieve performance whilst maintaining the PHS form in closed loop. This complements contemporary results in the literature, which preserve the open-loop shape variables. As a case study, we consider a robotic manipulator mounted on a flexible base and compensate for the motion of the base while positioning the end effector with respect to the ground reference. We compare the proposed control strategy with special cases that correspond to other energy shaping strategies previously proposed in the literature.

Quantitative stem-loop RT-PCR for detection of microRNAs

Plant microRNAs (miRNAs) are a class of endogenous small RNAs that are essential for plant development and survival. They arise from larger precursor RNAs with a characteristic hairpin structure and regulate gene activity by targeting mRNA transcripts for cleavage or translational repression. Efficient and reliable detection and quantification of miRNA expression has become an essential step in understanding their specific roles. The expression levels of miRNAs can vary dramatically between samples and they often escape detection by conventional technologies such as cloning, northern hybridization and microarray analysis. The stem-loop RT-PCR method described here is designed to detect and quantify mature miRNAs in a fast, specific, accurate and reliable manner. First, a miRNA-specific stem-loop RT primer is hybridized to the miRNA and then reverse transcribed. Next, the RT product is amplified and monitored in real time using a miRNA-specific forward primer and the universal reverse primer. This method enables miRNA expression profiling from as little as 10 pg of total RNA and is suitable for high-throughput miRNA expression analysis.

Investigating subspace distances in semantic spaces

Semantic space models of word meaning derived from co-occurrence statistics within a corpus of documents, such as the Hyperspace Analogous to Language (HAL) model, have been proposed in the past. While word similarity can be computed using these models, it is not clear how semantic spaces derived from different sets of documents can be compared. In this paper, we focus on this problem, and we revisit the proposal of using semantic subspace distance measurements [1]. In particular, we outline the research questions that still need to be addressed to investigate and validate these distance measures. Then, we describe our plans for future research.

An arteriovenous loop in a protected space generates a permanent, highly vascular, tissue-engineered construct

A major obstacle to 3-dimensional tissue engineering is incorporation of a functional vascular supply to support the expanding new tissue. This is overcome in an in vivo intrinsic vascularization model where an arteriovenous loop (AVL) is placed in a noncollapsible space protected by a polycarbonate chamber. Vascular development and hypoxia were examined from 3 days to 112 days by vascular casting, morphometric, and morphological techniques to understand the model's vascular growth and remodeling parameters for tissue engineering purposes. At 3 days a fibrin exudate surrounded the AVL, providing a scaffold to migrating inflammatory, endothelial, and mesenchymal cells. Capillaries formed between 3 and 7 days. Hypoxia and cell proliferation were maximal at 7 days, followed by a peak in percent vascular volume at 10 days (23.20±3.14% compared with 3.59±2.68% at 3 days, P<0.001). Maximal apoptosis was observed at 112 days. The protected space and spontaneous microcirculatory development in this model suggest it would be applicable for in vivo tissue engineering. A temporal window in a period of intense angiogenesis at 7 to 10 days is optimal for exogenous cell seeding and survival in the chamber, potentially enabling specific tissue outcomes to be achieved.

Semantic spaces : measuring the distance between different subspaces

Semantic Space models, which provide a numerical representation of words’ meaning extracted from corpus of documents, have been formalized in terms of Hermitian operators over real valued Hilbert spaces by Bruza et al. [1]. The collapse of a word into a particular meaning has been investigated applying the notion of quantum collapse of superpositional states [2]. While the semantic association between words in a Semantic Space can be computed by means of the Minkowski distance [3] or the cosine of the angle between the vector representation of each pair of words, a new procedure is needed in order to establish relations between two or more Semantic Spaces. We address the question: how can the distance between different Semantic Spaces be computed? By representing each Semantic Space as a subspace of a more general Hilbert space, the relationship between Semantic Spaces can be computed by means of the subspace distance. Such distance needs to take into account the difference in the dimensions between subspaces. The availability of a distance for comparing different Semantic Subspaces would enable to achieve a deeper understanding about the geometry of Semantic Spaces which would possibly translate into better effectiveness in Information Retrieval tasks.

Urban knowledge and innovation spaces : concepts, conditions, and contexts

Innovation is one of the key determinants of growth in the globalised knowledge economy, and ‘urban knowledge and innovation spaces’ form the spatial foci for sustained innovation. This paper aims to explore concepts, conditions and contexts that substantiate the development of these spaces of innovation. The paper seeks to identify the foundational elements of knowledge- based urban development to outline the concept of urban knowledge and innovation spaces, and justify its meaning, unique characteristics and growing influence in the contemporary cities. It rationalises the relevance of the three underlying conditions—namely policy, place, and people— to better understand their contribution in the development of such spaces. This paper sheds light over the varied contexts shaping each urban knowledge and innovation space uniquely. The paper reveals the interplay between design and policies that is required for the creation of spaces of innovation that are economically strong, socially connected, spatially stimulating, and environmentally sustainable.