The Day After Tomorrow: Transition Management, Spatial Planning & the Low Carbon Economy

Many of the societal challenges that current spatial planning practice claims to be addressing (climate change, peak oil, obesity, aging society etc) encompass issues and timescales that lie beyond the traditional scope planning policy (Campbell 2006). The example of achieving a low carbon economy typifies this in that it demands a process of society-wide transition, involving steering a wide range of factors (markets, infrastructure, governance, individual behaviour etc). Such a process offers a challenge to traditional approaches to planning as they cannot be guided by a fixed blueprint, given the timescales involved (up to 50 years) and an enhanced level of uncertainty, social resistance, lack of control over implementation and a danger of ‘policy lock in’ (Kemp et al 2007). One approach to responding to these challenges is the concept of transition management which has emerged from studies of science, technology and innovation (Geels 2002, Markard et al 2012). Although not without criticism, this perspective attempts to uncertainty and complexity encompassing long term visions that integrates multi-level, multi-actor and multi-domain perspectives (Rotmans et al 2001).
 
Given its origins, research on transition management has tended to neglect spatial contexts (Coenen et al 2012) and, related to this, it’s relationship with spatial planning is poorly understood. Using the example of the low carbon transition, this paper will review the relationships between the concepts, methodologies and goals of transition management and spatial planning to explore whether a closer integration of the two fields offers benefits to achieving the long term challenges facing society.
 

Fast Byzantine Leader Election in Dynamic Networks

We study the fundamental Byzantine leader election problem in dynamic networks where the topology can change from round to round and nodes can also experience heavy {\em churn} (i.e., nodes can join and leave the network continuously over time). We assume the full information model where the Byzantine nodes have complete knowledge about the entire state of the network at every round (including random choices made by all the nodes), have unbounded computational power and can deviate arbitrarily from the protocol. The churn is controlled by an adversary that has complete knowledge and control over which nodes join and leave and at what times and also may rewire the topology in every round and has unlimited computational power, but is oblivious to the random choices made by the algorithm. Our main contribution is an $O(\log^3 n)$ round algorithm that achieves Byzantine leader election under the presence of up to $O({n}^{1/2 - \epsilon})$ Byzantine nodes (for a small constant $\epsilon > 0$) and a churn of up to \\$O(\sqrt{n}/\poly\log(n))$ nodes per round (where $n$ is the stable network size).The algorithm elects a leader with probability at least $1-n^{-\Omega(1)}$ and guarantees that it is an honest node with probability at least $1-n^{-\Omega(1)}$; assuming the algorithm succeeds, the leader's identity will be known to a $1-o(1)$ fraction of the honest nodes. Our algorithm is fully-distributed, lightweight, and is simple to implement. It is also scalable, as it runs in polylogarithmic (in $n$) time and requires nodes to send and receive messages of only polylogarithmic size per round.To the best of our knowledge, our algorithm is the first scalable solution for Byzantine leader election in a dynamic network with a high rate of churn; our protocol can also be used to solve Byzantine agreement in a straightforward way.We also show how to implement an (almost-everywhere) public coin with constant bias in a dynamic network with Byzantine nodes and provide a mechanism for enabling honest nodes to store information reliably in the network, which might be of independent interest.

A simplified procedure for sizing solar thermal systems based on national assessment methods in the UK and Ireland.

Solar heating systems have the potential to be an efficient renewable energy technology, provided they are sized correctly. Sizing a solar thermal system for domestic applications does not warrant the cost of a simulation. As a result simplified sizing procedures are required. The size of a system depends on a number of variables including the efficiency of the collector itself, the hot water demand and the solar radiation at a given location. Domestic Hot Water (DHW) demand varies with time and is assessed using a multi-parameter detailed model. Secondly, the national energy evaluation methodologies are evaluated from the perspective of solar thermal system sizing. Based on the assessment of the standards, limitations in the evaluation method for solar thermal systems are outlined and an adapted method, specific to the sizing of solar thermal systems, is proposed. The methodology is presented for two common dwelling scenarios. Results from this showed that it is difficult to achieve a high solar fraction given practical sizes of system infrastructure (storage tanks) for standard domestic properties. However, solar thermal systems can significantly offset energy loads due associated DHW consumption, particularly when sized appropriately. The presented methodology is valuable for simple solar system design and also for the quick comparison of salient criteria.

Secrecy Performance of Wirelessly Powered Wiretap Channels

This paper considers a wirelessly powered wiretap channel, where an energy constrained multi-antenna information source, powered by a dedicated power beacon, communicates with a legitimate user in the presence of a passive eavesdropper. Based on a simple time-switching protocol where power transfer and information transmission are separated in time, we investigate two popular multi-antenna transmission schemes at the information source, namely maximum ratio transmission (MRT) and transmit antenna selection (TAS). Closed-form expressions are derived for the achievable secrecy outage probability and average secrecy rate for both schemes. In addition, simple approximations are obtained at the high signal-to-noise ratio (SNR) regime. Our results demonstrate that by exploiting the full knowledge of channel state information (CSI), we can achieve a better secrecy performance, e.g., with full CSI of the main channel, the system can achieve substantial secrecy diversity gain. On the other hand, without the CSI of the main channel, no diversity gain can be attained. Moreover, we show that the additional level of randomness induced by wireless power transfer does not affect the secrecy performance in the high SNR regime. Finally, our theoretical claims are validated by the numerical results.

Improving multi-site benefit functions via Bayesian model averaging: A new approach to benefit transfer

A benefit function transfer obtains estimates of willingness-to-pay (WTP) for the evaluation of a given policy at a site by combining existing information from different study sites. This has the advantage that more efficient estimates are obtained, but it relies on the assumption that the heterogeneity between sites is appropriately captured in the benefit transfer model. A more expensive alternative to estimate WTP is to analyze only data from the policy site in question while ignoring information from other sites. We make use of the fact that these two choices can be viewed as a model selection problem and extend the set of models to allow for the hypothesis that the benefit function is only applicable to a subset of sites. We show how Bayesian model averaging (BMA) techniques can be used to optimally combine information from all models. The Bayesian algorithm searches for the set of sites that can form the basis for estimating a benefit function and reveals whether such information can be transferred to new sites for which only a small data set is available. We illustrate the method with a sample of 42 forests from U.K. and Ireland. We find that BMA benefit function transfer produces reliable estimates and can increase about 8 times the information content of a small sample when the forest is 'poolable'. © 2008 Elsevier Inc. All rights reserved.

Entanglement distribution with global control in a star-shaped multi-splitter

Distributed quantum information processing (QIP) is a promising way to bypass problems due to unwanted interactions between elements. However, this strategy presupposes the engineering of protocols for remote processors. In many of them, pairwise entanglement is a key resource. We study a model which distributes entanglement among elements of a delocalized network without local control. The model is efficient both in finite- and infinite-dimensional Hilbert spaces. We suggest a setup of electromechanical systems to implement our proposal.

A possible model of benzimidazole binding to beta-tubulin disclosed by invoking an inter-domain movement.

Although it is well established that benzimidazole (BZMs) compounds exert their therapeutic effects through binding to helminth beta-tubulin and thus disrupting microtubule-based processes in the parasites, the precise location of the benzimidazole-binding site on the beta-tubulin molecule has yet to be determined. In the present study, we have used previous experimental data as cues to help identify this site. Firstly, benzimidazole resistance has been correlated with a phenylalanine-to-tyrosine substitution at position 200 of Haemonchus contortus beta-tubulin isotype-I. Secondly, site-directed mutagenesis studies, using fungi, have shown that other residues in this region of the protein can influence the interaction of benzimidazoles with beta-tubulin. However, the atomic structure of the alphabeta-tubulin dimer shows that residue 200 and the other implicated residues are buried within the protein. This poses the question: how might benzimidazoles interact with these apparently inaccessible residues? In the present study, we present a mechanism by which those residues generally believed to interact with benzimidazoles may become accessible to the drugs. Furthermore, by docking albendazole-sulphoxide into a modelled H. contortus beta-tubulin molecule we offer a structural explanation for how the mutation conferring benzimidazole resistance in nematodes may act, as well as a possible explanation for the species-specificity of benzimidazole anthelmintics.

Analogies between linguistics and information theory

An analogy is established between the syntagm and paradigm from Saussurean linguistics and the message and messages for selection from the information theory initiated by Claude Shannon. The analogy is pursued both as an end itself and for its analytic value in understanding patterns of retrieval from full text systems. The multivalency of individual words when isolated from their syntagm is contrasted with the relative stability of meaning of multi-word sequences, when searching ordinary written discourse. The syntagm is understood as the linear sequence of oral and written language. Saussureâ??s understanding of the word, as a unit which compels recognition by the mind, is endorsed, although not regarded as final. The lesser multivalency of multi-word sequences is understood as the greater determination of signification by the extended syntagm. The paradigm is primarily understood as the network of associations a word acquires when considered apart from the syntagm. The restriction of information theory to expression or signals, and its focus on the combinatorial aspects of the message, is sustained. The message in the model of communication in information theory can include sequences of written language. Shannonâ??s understanding of the written word, as a cohesive group of letters, with strong internal statistical influences, is added to the Saussurean conception. Sequences of more than one word are regarded as weakly correlated concatenations of cohesive units.

A decentralized model of information pricing in networks

We propose a recursive method of pricing an information good in a network of holders and demanders of this good. The prices are determined via a unique equilibrium outcome in a sequence of bilateral bargaining games that are played by connected agents. If the information is an homogenous, non-depreciating good without network effects we derive explicit formulae which elucidate the role of the link pattern among the players. Particularly, we find out that the equilibrium price is intimately related to the existence of cycles in the network: It is zero if a cycle covers the trading pair and it is proportional to the direct and indirect utility that the good generates otherwise.

A variational approach to the relaxation of single domain magnetic particles based on Brown's model

Brown's model for the relaxation of the magnetization of a single domain ferromagnetic particle is considered. This model results in the Fokker-Planck equation of the process. The solution of this equation in the cases of most interest is non- trivial. The probability density of orientations of the magnetization in the Fokker-Planck equation can be expanded in terms of an infinite set of eigenfunctions and their corresponding eigenvalues where these obey a Sturm-Liouville type equation. A variational principle is applied to the solution of this equation in the case of an axially symmetric potential. The first (non-zero) eigenvalue, corresponding to the largest time constant, is considered. From this we obtain two new results. Firstly, an approximate minimising trial function is obtained which allows calculation of a rigorous upper bound. Secondly, a new upper bound formula is derived based on the Euler-Lagrange condition. This leads to very accurate calculation of the eigenvalue but also, interestingly, from this, use of the simplest trial function yields an equivalent result to the correlation time of Coffey et at. and the integral relaxation time of Garanin. (C) 2004 Elsevier B.V. All rights reserved.

Towards agent-oriented model-driven architecture

Model Driven Architecture supports the transformation from reusable models to executable software. Business representations, however, cannot be fully and explicitly represented in such models for direct transformation into running systems. Thus, once business needs change, the language abstractions used by MDA (e.g. Object Constraint Language / Action Semantics), being low level, have to be edited directly. We therefore describe an Agent-oriented Model Driven Architecture (AMDA) that uses a set of business models under continuous maintenance by business people, reflecting the current business needs and being associated with adaptive agents that interpret the captured knowledge to behave dynamically. Three contributions of the AMDA approach are identified: 1) to Agent-oriented Software Engineering, a method of building adaptive Multi-Agent Systems; 2) to MDA, a means of abstracting high level business-oriented models to align executable systems with their requirements at runtime; 3) to distributed systems, the interoperability of disparate components and services via the agent abstraction.

Systematic Usage of Embedded Modelling Languages in Automated Model Transformation Chains

Annotation of programs using embedded Domain-Specific Languages (embedded DSLs), such as the program annotation facility for the Java programming language, is a well-known practice in computer science. In this paper we argue for and propose a specialized approach for the usage of embedded Domain-Specific Modelling Languages (embedded DSMLs) in Model-Driven Engineering (MDE) processes that in particular supports automated many-step model transformation chains. It can happen that information defined at some point, using an embedded DSML, is not required in the next immediate transformation step, but in a later one. We propose a new approach of model annotation enabling flexible many-step transformation chains. The approach utilizes a combination of embedded DSMLs, trace models and a megamodel. We demonstrate our approach based on an example MDE process and an industrial case study.