Articulating ‘public interest’ through complexity theory

The ‘Public interest’, even if viewed with ambiguity or scepticism, has been one of the primary means by which various professional roles of planners have been justified. Many objections to the concept have been advanced by writers in planning academia. Notwithstanding these, ‘public interest’ continues to be mobilised, to justify, defend or argue for planning interventions and reforms. This has led to arguments that planning will have to adopt and recognise some form of public interest in practice to legitimise itself.. This paper explores current debates around public interest and social justice and advances a vision of the public interest informed by complexity theory. The empirical context of the paper is the poverty alleviation programme, the Kudumbashree project in Kerala, India.

Managing the complexity of information flow for construction small and medium-sized enterprises (CSMEs) using system dynamics and collaborative technologies

With the increase in e-commerce and the digitisation of design data and information,the construction sector has become reliant upon IT infrastructure and systems. The design and production process is more complex, more interconnected, and reliant upon greater information mobility, with seamless exchange of data and information in real time. Construction small and medium-sized enterprises (CSMEs), in particular,the speciality contractors, can effectively utilise cost-effective collaboration-enabling technologies, such as cloud computing, to help in the effective transfer of information and data to improve productivity. The system dynamics (SD) approach offers a perspective and tools to enable a better understanding of the dynamics of complex systems. This research focuses upon system dynamics methodology as a modelling and analysis tool in order to understand and identify the key drivers in the absorption of cloud computing for CSMEs. The aim of this paper is to determine how the use of system dynamics (SD) can improve the management of information flow through collaborative technologies leading to improved productivity. The data supporting the use of system dynamics was obtained through a pilot study consisting of questionnaires and interviews from five CSMEs in the UK house-building sector.

Causation, complexity, and the concert: the pragmatics of causal explanation in international relations

A causal explanation provides information about the causal history of whatever is being explained. However, most causal histories extend back almost infinitely and can be described in almost infinite detail. Causal explanations therefore involve choices about which elements of causal histories to pick out. These choices are pragmatic: they reflect our explanatory interests. When adjudicating between competing causal explanations, we must therefore consider not only questions of epistemic adequacy (whether we have good grounds for identifying certain factors as causes) but also questions of pragmatic adequacy (whether the aspects of the causal history picked out are salient to our explanatory interests). Recognizing that causal explanations differ pragmatically as well as epistemically is crucial for identifying what is at stake in competing explanations of the relative peacefulness of the nineteenth-century Concert system. It is also crucial for understanding how explanations of past events can inform policy prescription.

Syntactic complexity in the comprehension of wh-questions and relative clauses in typical language development and autism

This study investigates effects of syntactic complexity operationalised in terms of movement, intervention and (NP) feature similarity in the development of A’ dependencies in 4-, 6-, and 8-year old typically developing (TD) French children and children with Autism Spectrum Disorders (ASD). Children completed an off-line comprehension task testing eight syntactic structures classified in four levels of complexity: Level 0: No Movement; Level 1: Movement without (configurational) Intervention; Level 2: Movement with Intervention from an element which is maximally different or featurally ‘disjoint’ (mismatched in both lexical NP restriction and number); Level 3: Movement with Intervention from an element similar in one feature or featurally ‘intersecting’ (matched in lexical NP restriction, mismatched in number). The results show that syntactic complexity affects TD children across the three age groups, but also indicate developmental differences between these groups. Movement affected all three groups in a similar way, but intervention effects in intersection cases were stronger in younger than older children, with NP feature similarity affecting only 4-year olds. Complexity effects created by the similarity in lexical restriction of an intervener thus appear to be overcome early in development, arguably thanks to other differences of this intervener (which was mismatched in number). Children with ASD performed less well than the TD children although they were matched on non-verbal reasoning. Overall, syntactic complexity affected their performance in a similar way as in their TD controls, but their performance correlated with non-verbal abilities rather than age, suggesting that their grammatical development does not follow the smooth relation to age that is found in TD children.

Brief behavioural activation for adolescent depression: working with complexity and risk

Given the long-term negative outcomes associated with depression in adolescence, there is a pressing need to develop brief, evidence based treatments that are accessible to more young people experiencing low mood. Behavioural Activation (BA) is an effective treatment for adult depression, however little research has focused on the use of BA with depressed adolescents, particularly with briefer forms of BA. In this article we outline an adaptation of brief Behavioral Activation Treatment of Depression (BATD) designed for adolescents and delivered in eight sessions (Brief BA). This case example illustrates how a structured, brief intervention was useful for a depressed young person with a number of complicating and risk factors.

The oscillatory bioelectrical signal from plants explained by a simulated electrical model and tested using Lempel-Ziv complexity

This paper demonstrates the oscillatory characteristics of electrical signals acquired from two ornamental plant types (Epipremnum pinnatum and Philodendron scandens - Family Araceae), using a noninvasive acquisition system. The electrical signal was recorded using Ag/AgCl superficial electrodes inside a Faraday cage. The presence of the oscillatory electric generator was shown using a classical power spectral density. The Lempel and Ziv complexity measurement showed that the plant signal was not noise despite its nonlinear behavior. The oscillatory characteristics of the signal were explained using a simulated electrical model that establishes that for a frequency range from 5 to 15 Hz, the oscillatory characteristic is higher than for other frequency ranges. All results show that non-invasive electrical plant signals can be acquired with improvement of signal-to-noise ratio using a Faraday cage, and a simple electrical model is able to explain the electrical signal being generated. (C) 2010 Elsevier B.V. All rights reserved.

Coding behavioural data for cladistic analysis: using dynamic homology without parsimony

Many of the controversies around the concept of homology rest on the subjectivity inherent to primary homology propositions. Dynamic homology partially solves this problem, but there has been up to now scant application of it outside of the molecular domain. This is probably because morphological and behavioural characters are rich in properties, connections and qualities, so that there is less space for conflicting character delimitations. Here we present a new method for the direct optimization of behavioural data, a method that relies on the richness of this database to delimit the characters, and on dynamic procedures to establish character state identity. We use between-species congruence in the data matrix and topological stability to choose the best cladogram. We test the methodology using sequences of predatory behaviour in a group of spiders that evolved the highly modified predatory technique of spitting glue onto prey. The cladogram recovered is fully compatible with previous analyses in the literature, and thus the method seems consistent. Besides the advantage of enhanced objectivity in character proposition, the new procedure allows the use of complex, context-dependent behavioural characters in an evolutionary framework, an important step towards the practical integration of the evolutionary and ecological perspectives on diversity. (C) The Willi Hennig Society 2010.

The non-coding RNA BC1 is down-regulated in the hippocampus of Wistar Audiogenic Rat (WAR) strain after audiogenic kindling

The aim of this study was to identify molecular pathways involved in audiogenic seizures in the epilepsy-prone Wistar Audiogenic Rat (WAR). For this, we used a suppression-subtractive hybridization (SSH) library from the hippocampus of WARs coupled to microarray comparative gene expression analysis, followed by Northern blot validation of individual genes. We discovered that the levels of the non-protein coding (npc) RNA BC1 were significantly reduced in the hippocampus of WARs submitted to repeated audiogenic seizures (audiogenic kindling) when compared to Wistar resistant rats and to both naive WARs and Wistars. By quantitative in situ hybridization, we verified lower levels of BC1 RNA in the GD-hilus and significant signal ratio reduction in the stratum radiatum and stratum pyramidale of hippocampal CA3 subfield of audiogenic kindled animals. Functional results recently obtained in a BC1-/- mouse model and our current data are supportive of a potential disruption in signaling pathways, upstream of BC1, associated with the seizure susceptibility of WARs. (C) 2010 Elsevier B.V. All rights reserved.

Medical image retrieval based on complexity analysis

Texture is one of the most important visual attributes used in image analysis. It is used in many content-based image retrieval systems, where it allows the identification of a larger number of images from distinct origins. This paper presents a novel approach for image analysis and retrieval based on complexity analysis. The approach consists of a texture segmentation step, performed by complexity analysis through BoxCounting fractal dimension, followed by the estimation of complexity of each computed region by multiscale fractal dimension. Experiments have been performed with MRI database in both pattern recognition and image retrieval contexts. Results show the accuracy of the method and also indicate how the performance changes as the texture segmentation process is altered.

Complexity and anisotropy in host morphology make populations less susceptible to epidemic outbreaks

One of the challenges in epidemiology is to account for the complex morphological structure of hosts such as plant roots, crop fields, farms, cells, animal habitats and social networks, when the transmission of infection occurs between contiguous hosts. Morphological complexity brings an inherent heterogeneity in populations and affects the dynamics of pathogen spread in such systems. We have analysed the influence of realistically complex host morphology on the threshold for invasion and epidemic outbreak in an SIR (susceptible-infected-recovered) epidemiological model. We show that disorder expressed in the host morphology and anisotropy reduces the probability of epidemic outbreak and thus makes the system more resistant to epidemic outbreaks. We obtain general analytical estimates for minimally safe bounds for an invasion threshold and then illustrate their validity by considering an example of host data for branching hosts (salamander retinal ganglion cells). Several spatial arrangements of hosts with different degrees of heterogeneity have been considered in order to separately analyse the role of shape complexity and anisotropy in the host population. The estimates for invasion threshold are linked to morphological characteristics of the hosts that can be used for determining the threshold for invasion in practical applications.

Single Synapse Information Coding in Intraburst Spike Patterns of Central Pattern Generator Motor Neurons

Burst firing is ubiquitous in nervous systems and has been intensively studied in central pattern generators (CPGs). Previous works have described subtle intraburst spike patterns (IBSPs) that, despite being traditionally neglected for their lack of relation to CPG motor function, were shown to be cell-type specific and sensitive to CPG connectivity. Here we address this matter by investigating how a bursting motor neuron expresses information about other neurons in the network. We performed experiments on the crustacean stomatogastric pyloric CPG, both in control conditions and interacting in real-time with computer model neurons. The sensitivity of postsynaptic to presynaptic IBSPs was inferred by computing their average mutual information along each neuron burst. We found that details of input patterns are nonlinearly and inhomogeneously coded through a single synapse into the fine IBSPs structure of the postsynaptic neuron following burst. In this way, motor neurons are able to use different time scales to convey two types of information simultaneously: muscle contraction (related to bursting rhythm) and the behavior of other CPG neurons (at a much shorter timescale by using IBSPs as information carriers). Moreover, the analysis revealed that the coding mechanism described takes part in a previously unsuspected information pathway from a CPG motor neuron to a nerve that projects to sensory brain areas, thus providing evidence of the general physiological role of information coding through IBSPs in the regulation of neuronal firing patterns in remote circuits by the CNS.

Recording from Two Neurons: Second-Order Stimulus Reconstruction from Spike Trains and Population Coding

We study the reconstruction of visual stimuli from spike trains, representing the reconstructed stimulus by a Volterra series up to second order. We illustrate this procedure in a prominent example of spiking neurons, recording simultaneously from the two H1 neurons located in the lobula plate of the fly Chrysomya megacephala. The fly views two types of stimuli, corresponding to rotational and translational displacements. Second-order reconstructions require the manipulation of potentially very large matrices, which obstructs the use of this approach when there are many neurons. We avoid the computation and inversion of these matrices using a convenient set of basis functions to expand our variables in. This requires approximating the spike train four-point functions by combinations of two-point functions similar to relations, which would be true for gaussian stochastic processes. In our test case, this approximation does not reduce the quality of the reconstruction. The overall contribution to stimulus reconstruction of the second-order kernels, measured by the mean squared error, is only about 5% of the first-order contribution. Yet at specific stimulus-dependent instants, the addition of second-order kernels represents up to 100% improvement, but only for rotational stimuli. We present a perturbative scheme to facilitate the application of our method to weakly correlated neurons.