Dynamic scale theory for characterizing surface morphology of layer-by-layer films of poly(o-methoxyaniline)

The dynamic scale theory and fractal concepts are employed in the characterization of surface morphological properties of layer-by-layer (LBL) films from poly(o-methoxyaniline) (POMA) alternated with poly(vinyl sulfonic acid) (PVS). The fractal dimensions are found to depend on the procedures to fabricate the POMA/PVS multilayers, particularly with regard to the drying procedures. LBL films obtained via drying in ambient air show a more homogeneous surface, compared to films dried under vacuum or a flow of nitrogen, due to a uniform rearrangement of polymer molecules during solvent evaporation.

Front spreading in population dynamic models. Theory and application to the Neolithic transition

This thesis presents population dynamics models that can be applied to predict the rate of spread of the Neolithic transition (change from hunter-gathering to farming economics) across the European continent, which took place about 9000 to 5000 years ago. The first models in this thesis provide predictions at a continental scale. We develop population dynamics models with explicit kernels and apply realistic data. We also derive a new time-delayed reaction-diffusion equation which yields speeds about a 10% slower than previous models. We also deal with a regional variability: the slowdown of the Neolithic front when reaching the North of Europe. We develop simple reaction-diffusion models that can predict the measured speeds in terms of the non-homogeneous distribution of pre-Neolithic (Mesolithic) population in Europe, which were present in higher densities at the North of the continent. Such models can explain the observed speeds.

Learning processes in creative service teams : towards a dynamic systems theory

The fastest-growing segment of jobs in the creative sector are in those firms that provide creative services to other sectors (Hearn, Goldsmith, Bridgstock, Rodgers 2014, this volume; Cunningham 2014, this volume). There are also a large number of Creative Services (Architecture and Design, Advertising and Marketing, Software and Digital Content occupations) workers embedded in organizations in other industry sectors (Cunningham and Higgs 2009). Ben Goldsmith (2014, this volume) shows, for example, that the Financial Services sector is the largest employer of digital creative talent in Australia. But why should this be? We argue it is because ‘knowledge-based intangibles are increasingly the source of value creation and hence of sustainable competitive advantage (Mudambi 2008, 186). This value creation occurs primarily at the research and development (R and D) and the marketing ends of the supply chain. Both of these areas require strong creative capabilities in order to design for, and to persuade, consumers. It is no surprise that Jess Rodgers (2014, this volume), in a study of Australia’s Manufacturing sector, found designers and advertising and marketing occupations to be the most numerous creative occupations. Greg Hearn and Ruth Bridgstock (2013, forthcoming) suggest ‘the creative heart of the creative economy […] is the social and organisational routines that manage the generation of cultural novelty, both tacit and codified, internal and external, and [cultural novelty’s] combination with other knowledges […] produce and capture value’. 2 Moreover, the main “social and organisational routine” is usually a team (for example, Grabher 2002; 2004).

Planning “Discrete” Movements Using a Continuous System: Insights from a Dynamic Field Theory of Movement Preparation

The timed-initiation paradigm developed by Ghez and colleagues (1997) has revealed two modes of motor planning: continuous and discrete. Continuous responding occurs when targets are separated by less than 60° of spatial angle, and discrete responding occurs when targets are separated by greater than 60°. Although these two modes are thought to reflect the operation of separable strategic planning systems, a new theory of movement preparation, the Dynamic Field Theory, suggests that two modes emerge flexibly from the same system. Experiment 1 replicated continuous and discrete performance using a task modified to allow for a critical test of the single system view. In Experiment 2, participants were allowed to correct their movements following movement initiation (the standard task does not allow corrections). Results showed continuous planning performance at large and small target separations. These results are consistent with the proposal that the two modes reflect the time-dependent “preshaping” of a single planning system.

Generalizing the dynamic field theory of spatial cognition across real and developmental time scales

Within cognitive neuroscience, computational models are designed to provide insights into the organization of behavior while adhering to neural principles. These models should provide sufficient specificity to generate novel predictions while maintaining the generality needed to capture behavior across tasks and/or time scales. This paper presents one such model, the Dynamic Field Theory (DFT) of spatial cognition, showing new simulations that provide a demonstration proof that the theory generalizes across developmental changes in performance in four tasks—the Piagetian A-not-B task, a sandbox version of the A-not-B task, a canonical spatial recall task, and a position discrimination task. Model simulations demonstrate that the DFT can accomplish both specificity—generating novel, testable predictions—and generality—spanning multiple tasks across development with a relatively simple developmental hypothesis. Critically, the DFT achieves generality across tasks and time scales with no modification to its basic structure and with a strong commitment to neural principles. The only change necessary to capture development in the model was an increase in the precision of the tuning of receptive fields as well as an increase in the precision of local excitatory interactions among neurons in the model. These small quantitative changes were sufficient to move the model through a set of quantitative and qualitative behavioral changes that span the age range from 8 months to 6 years and into adulthood. We conclude by considering how the DFT is positioned in the literature, the challenges on the horizon for our framework, and how a dynamic field approach can yield new insights into development from a computational cognitive neuroscience perspective.

Tests of the Dynamic Field Theory and the Spatial Precision Hypothesis: Capturing a Qualitative Developmental Transition in Spatial Working Memory

This study tested a dynamic field theory (DFT) of spatial working memory and an associated spatial precision hypothesis (SPH). Between 3 and 6 years of age, there is a qualitative shift in how children use reference axes to remember locations: 3-year-olds’ spatial recall responses are biased toward reference axes after short memory delays, whereas 6-year-olds’ responses are biased away from reference axes. According to the DFT and the SPH, quantitative improvements over development in the precision of excitatory and inhibitory working memory processes lead to this qualitative shift. Simulations of the DFT in Experiment 1 predict that improvements in precision should cause the spatial range of targets attracted toward a reference axis to narrow gradually over development, with repulsion emerging and gradually increasing until responses to most targets show biases away from the axis. Results from Experiment 2 with 3- to 5-year-olds support these predictions. Simulations of the DFT in Experiment 3 quantitatively fit the empirical results and offer insights into the neural processes underlying this developmental change.

Morphological characterization of Langmuir-Blodgett films from polyaniline and a ruthenium complex (Rupy): influence of the relative concentration of Rupy

We report on the use of dynamic scale theory and fractal analyses in a study of the growth stages of Langmuir-Blodgett (LB) films of polyaniline and a neutral biphosphinic ruthenium complex, namely mer-[ RuCl3 (dppb)(py)] (dppb = 1,4-bis(diphenylphosphine) buthane, py = pyridine), Rupy. The LB films were deposited onto indium-tin-oxide substrates and characterized with atomic force microscopy. From the granular morphology exhibited by the films one could infer growth processes inside and outside the grains. Growth outside was found to follow the Kardar-Parisi-Zhang model, with fractal dimensions of about 2.7. As one would expect, inside the grains the morphology is close to a Euclidian surface with fractal dimension of about 2.

Morphology characterization of layer-by-layer films from PAH/MA-co-DR13: the role of film thickness

We report on the use of dynamic scale theory and fractal analyses in the Study of distinct growth stages of layer-by-layer (LBL) films of poly(allylamine hydrochloride) (PAH) and a side-chain-substituted azobenzene copolymer (Ma-co-DR13). The LBL films were adsorbed oil glass substrates and characterized with atomic force microscopy with the Ma-co-DR13 at the top layer. The ganular morphology exhibited by the films allowed the observation of the growth process inside and outside the grains. The growth outside the grains was found to follow the Kardar-Parisi-Zhang model, with fractal dimensions of ca. 2.6. One could expect that inside the grains the morphology would be close to a Euclidian surface with fractal dimension of ca. 2 for any growth stage. The latter, however, was observed only for thicker films containing more than 10 bilayers. For thinner films the morphology was well described by a self-affine fractal. Such dependence of the growth behavior with the film thickness is associated with a more complete coverage of adsorption sites in thicker films due to diffusion of polymer molecules. (c) 2004 Elsevier B.V. All rights reserved.

The impact of brand owner on consumers' brand perceptions : a development of Heider's Balance Theory

Studies have shown that the brand “owner” is very influential in positioning the brand and when the brand “owner” ceases his or her active role the brand will be perceived differently by the consumers. Balance Theory (HBT), a cognitive psychological theory, studies the triadic relationships between two persons and an entity and predicts that when a person’s original perception of the relationship is disturbed, the person restructures to a new balanced perception. Consequently, this research was undertaken to: conceptualize the brand owner’s impact on consumer’s brand perception; test the applicability of both the static and dynamic predictions of the Heider’s Balance Theory in brand owner-consumer-brand relation (OCB); construct and test a model of brand owner-consumer-brand relation; and examine if personality has an influence on OCB. A discovery-oriented approach was taken to understand the selected market segment, the ready-to-wear and diffusion lines of international designer labels. Chinese Brand Personality Scale, fashion proneness and hedonic and utilitarian shopping scales were developed, and validated. 51 customers were surveyed. Both traditional and extended methods used in the Balance Theory were employed in this study. Responses to liked brand have been used to test and develop the model, while those for disliked brand were used for test and confirmation. A “what if’ experimental approach was employed to test the applicability of dynamic HBT theory in OCB Model. The hypothesized OCB Model has been tested and validated. Consumers have been found to have separate views on the brand and the brand owner; and their responses to contrasting ethical and non-ethical news of the brand owner are different. Personality has been found to have an influence and two personality adapted models have been tested and validated. The actual results go beyond the prediction of the Balance Theory. Dominant triple positive balance mode, dominant negative balance mode, and mode of extreme antipathy have been found. It has been found that not all balanced modes are good for the brand. Contrary to Heider’s findings, simply liking may not necessarily lead to unit relation in the OCB Model.

Towards a Dynamic IS Function

With the growing importance of IS for organizations and the continuous stream of new IT developments, the IS function in organizations becomes more critical but is also more challenged. For example, how should the IS function deal with the consumerization of IT or what is the added value of the IS function when it comes to SaaS and the Cloud? In this paper we argue that IS research is in need of a dynamic perspective on the IS function. The IS function has to become more focused on building and adapting IS capabilities in a changing environment. We discuss that there has been an overreliance on the Resource Based View so far for understanding the IS function and capabilities and introduce Dynamic Capabilities Theory as an additional theoretical perspective, which has only been limitedly addressed in IS literature yet. We present a first conceptualization of the dynamic IS function and discuss IS capabilities frameworks and individual IS capabilities from a dynamic perspective. These initial insights demonstrate the contribution of a dynamic perspective on the IS function itself.

Information geometry theory of high-dimension space and application for speaker independent continuous digit speech recognition

In the light of descriptive geometry and notions in set theory, this paper re-defines the basic elements in space such as curve and surface and so on, presents some fundamental notions with respect to the point cover based on the High-dimension space (HDS) point covering theory, finally takes points from mapping part of speech signals to HDS, so as to analyze distribution information of these speech points in HDS, and various geometric covering objects for speech points and their relationship. Besides, this paper also proposes a new algorithm for speaker independent continuous digit speech recognition based on the HDS point dynamic searching theory without end-points detection and segmentation. First from the different digit syllables in real continuous digit speech, we establish the covering area in feature space for continuous speech. During recognition, we make use of the point covering dynamic searching theory in HDS to do recognition, and then get the satisfying recognized results. At last, compared to HMM (Hidden Markov models)-based method, from the development trend of the comparing results, as sample amount increasing, the difference of recognition rate between two methods will decrease slowly, while sample amount approaching to be very large, two recognition rates all close to 100% little by little. As seen from the results, the recognition rate of HDS point covering method is higher than that of in HMM (Hidden Markov models) based method, because, the point covering describes the morphological distribution for speech in HDS, whereas HMM-based method is only a probability distribution, whose accuracy is certainly inferior to point covering.

A Fractional Perspective to the Bond Graph Modelling of World Economies

Inspired in dynamic systems theory and Brewer’s contributions to apply it to economics, this paper establishes a bond graph model. Two main variables, a set of inter-connectivities based on nodes and links (bonds) and a fractional order dynamical perspective, prove to be a good macro-economic representation of countries’ potential performance in nowadays globalization. The estimations based on time series for 50 countries throughout the last 50 decades confirm the accuracy of the model and the importance of scale for economic performance.

Inverse problems in dynamic cognitive modeling

Inverse problems for dynamical system models of cognitive processes comprise the determination of synaptic weight matrices or kernel functions for neural networks or neural/dynamic field models, respectively. We introduce dynamic cognitive modeling as a three tier top-down approach where cognitive processes are first described as algorithms that operate on complex symbolic data structures. Second, symbolic expressions and operations are represented by states and transformations in abstract vector spaces. Third, prescribed trajectories through representation space are implemented in neurodynamical systems. We discuss the Amari equation for a neural/dynamic field theory as a special case and show that the kernel construction problem is particularly ill-posed. We suggest a Tikhonov-Hebbian learning method as regularization technique and demonstrate its validity and robustness for basic examples of cognitive computations.