A natural model for architecture

In John Frazer's seminal book An Evolutionary Architecture (1995), from which this essay is extracted, a fundamental approach is established for have natural systems can unfold mechanisms for negotiating the complex design space inherent in architectural systems. In this essay, which forms a critical part of the book, Frazer draws both correlations and distinctions from natural processes as emulated in design processes and form as active manifestations within natural systems. Form is seen as an evolving agent generated via the rules of descriptive genetic coding, functioning as a part of a metabolic environment. Frazer's process-model establishes the realm in which computation must manoeuvre to produce a valid solution space, including the operations of self-organisation, complexity and emergent behaviour. Addressing design as an authored practice, he extends the transference of 'creativity' from the explicit impression into form, to the investment of though, organisation and strategy in the computational processes which produce form. Frazer's text concentrates astutely on the practising of the evolutionary paradigm, the output of which postulates an architecture born of the relationships to dynamic environmental and socio-economic contexts, and realised through morphogenetic materialisation.

Realizing benefits from enterprise architecture : a measurement model

Enterprise architecture (EA) management has become an intensively discussed approach to manage enterprise transformations. Despite the popularity and potential of EA, both researchers and practitioners lament a lack of knowledge about the realization of benefits from EA. To determine the benefits from EA, we explore the various dimensions of EA benefit realization and report on the development of a validated and robust measurement instrument. In this paper, we test the reliability and construct validity of the EA benefit realization model (EABRM), which we have designed based on the DeLone & McLean IS success model and findings from exploratory interviews. A confirmatory factor analysis confirms the existence of an impact of five distinct and individually important dimensions on the benefits derived from EA: EA artefact quality, EA infrastructure quality, EA service quality, EA culture, and EA use. The analysis presented in this paper shows that the EA benefit realization model is an instrument that demonstrates strong reliability and validity.

A general model for host plant selection in phytophagous insects

We develop a general theoretical framework for exploring the host plant selection behaviour of herbivorous insects. This model can be used to address a number of questions, including the evolution of specialists, generalists, preference hierarchies, and learning. We use our model to: (i) demonstrate the consequences of the extent to which the reproductive success of a foraging female is limited by the rate at which they find host plants (host limitation) or the number of eggs they carry (egg limitation); (ii) emphasize the different consequences of variation in behaviour before and after landing on (locating) a host (termed pre- and post-alighting, respectively); (iii) show that, in contrast to previous predictions, learning can be favoured in post-alighting behaviour--in particular, individuals can be selected to concentrate oviposition on an abundant low-quality host, whilst ignoring a rare higher-quality host; (iv) emphasize the importance of interactions between mechanisms in favouring specialization or learning.

How host plant variability influences the advantages to learning : a theoretical model for oviposition behaviour in Lepidoptera

Learning can allow individuals to increase their fitness in particular environments. The advantage to learning depends on the predictability of the environment and the extent to which animals can adjust their behaviour. Earlier general models have investigated when environmental predictability might favour the evolution of learning in foraging animals. Here, we construct a theoretical model that predicts the advantages to learning using a specific biological example: oviposition in the Lepidoptera. Our model includes environmental and behavioural complexities relevant to host selection in these insects and tests whether the predictions of the general models still hold. Our results demonstrate how the advantage of learning is maximised when within-generation variability is minimised (the local environment consists mainly of a single host plant species) and between-generation variability is maximised (different host plant species are the most common in different generations). We discuss how our results: (a) can be applied to recent empirical work in different lepidopteran species and (b) predict an important role of learning in lepidopteran agricultural pests.

Service-oriented architecture integration within enterprise architecture : a-priori model

This paper proposes that critical realism can provide a useful theoretical foundation to study enterprise architecture (EA) evolution. Specifically it will investigate the practically relevant and academically challenging question of how EAs integrate the Service-oriented Architecture (SOA). Archer’s Morphogenetic theory is used as an analytical approach to distinguish the architectural conditions under which SOA is introduced, to study the relationships between these conditions and SOA introduction, and to reflect on EA evolution (elaborations) that then take place. The focus lies on the reasons why EA evolution takes place (or not) and what architectural changes happen. This paper uses the findings of a literature review to build an a-priori model informed by Archer’s theory to understand EA evolution in a field that often lacks a solid theoretical groundwork. The findings are threefold. First, EA can evolve on different levels (different integration outcomes). Second, the integration outcomes are classified into three levels: business architecture, information systems architecture and technology architecture. Third, the analytical separation using Archer’s theory is helpful in order to understand how these different integration outcomes are generated.

A model of enterprise architecture evolution

Enterprise architectures are exposed to fast emerging business and information technology capabilities. A prominent example is the paradigm of service-orientation, which leads to its own architectural requirements and impacts the design and ongoing evolution of Enterprise Architectures. This thesis develops the first theoretical model describing enterprise architecture evolution and outcomes in light of a changing IT landscape such as service-oriented architectures. The developed theoretical model explains enterprise architecture evolution, its main stages and related capabilities. This model can be used to derive theoretical, sound guidelines to manage enterprise architectures in a changing environment.

A meshfree model for plant tissue deformations during drying

Plant tissue has a complex cellular structure which is an aggregate of individual cells bonded by middle lamella. During drying processes, plant tissue undergoes extreme deformations which are mainly driven by moisture removal and turgor loss. Numerical modelling of this problem becomes challenging when conventional grid-based modelling techniques such as Finite Element Methods (FEM) and Finite Difference Methods (FDM) have grid-based limitations. This work presents a meshfree approach to model and simulate the deformations of plant tissues during drying. This method demonstrates the fundamental capabilities of meshfree methods in handling extreme deformations of multiphase systems. A simplified 2D tissue model is developed by aggregating individual cells while accounting for the stiffness of the middle lamella. Each individual cell is simply treated as consisting of two main components: cell fluid and cell wall. The cell fluid is modelled using Smoothed Particle Hydrodynamics (SPH) and the cell wall is modelled using a Discrete Element Method (DEM). During drying, moisture removal is accounted for by reduction of cell fluid and wall mass, which causes local shrinkage of cells eventually leading to tissue scale shrinkage. The cellular deformations are quantified using several cellular geometrical parameters and a favourably good agreement is observed when compared to experiments on apple tissue. The model is also capable of visually replicating dry tissue structures. The proposed model can be used as a step in developing complex tissue models to simulate extreme deformations during drying.

A particle based model to simulate microscale morphological changes of plant tissues during drying

Fundamental understanding on microscopic physical changes of plant materials is vital to optimize product quality and processing techniques, particularly in food engineering. Although grid-based numerical modelling can assist in this regard, it becomes quite challenging to overcome the inherited complexities of these biological materials especially when such materials undergo critical processing conditions such as drying, where the cellular structure undergoes extreme deformations. In this context, a meshfree particle based model was developed which is fundamentally capable of handling extreme deformations of plant tissues during drying. The model is built by coupling a particle based meshfree technique: Smoothed Particle Hydrodynamics (SPH) and a Discrete Element Method (DEM). Plant cells were initiated as hexagons and aggregated to form a tissue which also accounts for the characteristics of the middle lamella. In each cell, SPH was used to model cell protoplasm and DEM was used to model the cell wall. Drying was incorporated by varying the moisture content, the turgor pressure, and cell wall contraction effects. Compared to the state of the art grid-based microscale plant tissue drying models, the proposed model can be used to simulate tissues under excessive moisture content reductions incorporating cell wall wrinkling. Also, compared to the state of the art SPH-DEM tissue models, the proposed model better replicates real tissues and the cell-cell interactions used ensure efficient computations. Model predictions showed good agreement both qualitatively and quantitatively with experimental findings on dried plant tissues. The proposed modelling approach is fundamentally flexible to study different cellular structures for their microscale morphological changes at dehydration.

Using enterprise information architecture methods to model wicked problems in information systems design research

Design Science is the process of solving ‘wicked problems’ through designing, developing, instantiating, and evaluating novel solutions (Hevner, March, Park and Ram, 2004). Wicked problems are described as agent finitude in combination with problem complexity and normative constraint (Farrell and Hooker, 2013). In Information Systems Design Science, determining that problems are ‘wicked’ differentiates Design Science research from Solutions Engineering (Winter, 2008) and is a necessary part of proving the relevance to Information Systems Design Science research (Hevner, 2007; Iivari, 2007). Problem complexity is characterised as many problem components with nested, dependent and co-dependent relationships interacting through multiple feedback and feed-forward loops. Farrell and Hooker (2013) specifically state for wicked problems “it will often be impossible to disentangle the consequences of specific actions from those of other co-occurring interactions”. This paper discusses the application of an Enterprise Information Architecture modelling technique to disentangle the wicked problem complexity for one case. It proposes that such a modelling technique can be applied to other wicked problems and can lay the foundations for proving relevancy to DSR, provide solution pathways for artefact development, and aid to substantiate those elements required to produce Design Theory.

A coupled SPH-DEM model for micro-scale structural deformations of plant cells during drying

A single plant cell was modeled with smoothed particle hydrodynamics (SPH) and a discrete element method (DEM) to study the basic micromechanics that govern the cellular structural deformations during drying. This two-dimensional particle-based model consists of two components: a cell fluid model and a cell wall model. The cell fluid was approximated to a highly viscous Newtonian fluid and modeled with SPH. The cell wall was treated as a stiff semi-permeable solid membrane with visco-elastic properties and modeled as a neo-Hookean solid material using a DEM. Compared to existing meshfree particle-based plant cell models, we have specifically introduced cell wall–fluid attraction forces and cell wall bending stiffness effects to address the critical shrinkage characteristics of the plant cells during drying. Also, a moisture domain-based novel approach was used to simulate drying mechanisms within the particle scheme. The model performance was found to be mainly influenced by the particle resolution, initial gap between the outermost fluid particles and wall particles and number of particles in the SPH influence domain. A higher order smoothing kernel was used with adaptive smoothing length to improve the stability and accuracy of the model. Cell deformations at different states of cell dryness were qualitatively and quantitatively compared with microscopic experimental findings on apple cells and a fairly good agreement was observed with some exceptions. The wall–fluid attraction forces and cell wall bending stiffness were found to be significantly improving the model predictions. A detailed sensitivity analysis was also done to further investigate the influence of wall–fluid attraction forces, cell wall bending stiffness, cell wall stiffness and the particle resolution. This novel meshfree based modeling approach is highly applicable for cellular level deformation studies of plant food materials during drying, which characterize large deformations.

The multivariate A/C/E model and the genetics of fiber architecture

We present a new algorithm to compute the voxel-wise genetic contribution to brain fiber microstructure using diffusion tensor imaging (DTI) in a dataset of 25 monozygotic (MZ) twins and 25 dizygotic (DZ) twin pairs (100 subjects total). First, the structural and DT scans were linearly co-registered. Structural MR scans were nonlinearly mapped via a 3D fluid transformation to a geometrically centered mean template, and the deformation fields were applied to the DTI volumes. After tensor re-orientation to realign them to the anatomy, we computed several scalar and multivariate DT-derived measures including the geodesic anisotropy (GA), the tensor eigenvalues and the full diffusion tensors. A covariance-weighted distance was measured between twins in the Log-Euclidean framework [2], and used as input to a maximum-likelihood based algorithm to compute the contributions from genetics (A), common environmental factors (C) and unique environmental ones (E) to fiber architecture. Quanititative genetic studies can take advantage of the full information in the diffusion tensor, using covariance weighted distances and statistics on the tensor manifold.

Lack of release of bound anthocyanins and phenolic acids from carrot plant cell walls and model composites during simulated gastric and small intestinal digestion

Separately, polyphenols and plant cell walls (PCW) are important contributors to the health benefits associated with fruits and vegetables. However, interactions with PCW which occur either during food preparation or mastication may affect bioaccessibility and hence bioavailability of polyphenols. Binding interactions between anthocyanins, phenolic acids (PAs) and PCW components, were evaluated using both a bacterial cellulose-pectin model system and a black carrot puree system. The majority of available polyphenols bound to PCW material with 60-70% of available anthocyanins and PAs respectively binding to black carrot puree PCW matter. Once bound, release of polyphenols using acidified methanol is low with only similar to 20% of total anthocyanins to similar to 30% of PAs being released. Less than 2% of bound polyphenol was released after in vitro gastric and small intestinal (S.I.) digestion for both the model system and the black carrot puree PCW matter. Confocal laser scanning microscopy shows localised binding of anthocyanins to PCW. Very similar patterns of binding for anthocyanins and PAs suggest that PAs form complexes with anthocyanins and polysaccharides. Time dependent changes in extractability with acidified methanol but not the total bound fraction suggests that initial nonspecific deposition on cellulose surfaces is followed by rearrangement of the bound molecules. Minimal release of anthocyanins and PAs after simulated gastric and S.I. digestion indicates that polyphenols in fruits and vegetables which bind to the PCW will be transported to the colon where they would be expected to be released by the action of cell wall degrading bacteria.

Variation in water extraction with maize plant density and its impact on model application

The use of maize simulation models to determine the optimum plant population for rainfed environments allows the evaluation of plant populations over multiple years and locations at a lower cost than traditional field experimentation. However the APSIM maize model that has been used to conduct some of these 'virtual' experiments assumes that the maximum rate of soil water extraction by the crop root system is constant across plant populations. This untested assumption may cause grain yield to be overestimated in lower plant populations. A field experiment was conducted to determine whether maximum rates of water extraction vary with plant population, and the maximum rate of soil water extraction was estimated for three plant populations (2.4, 3.5 and 5.5 plants m(-2)) under water limited conditions. Maximum soil water extraction rates in the field experiment decreased linearly with plant population, and no difference was detected between plant populations for the crop lower limit of soil water extraction. Re-analysis of previous maize simulation experiments demonstrated that the use of inappropriately high extraction-rate parameters at low plant populations inflated predictions of grain yield, and could cause erroneous recommendations to be made for plant population. The results demonstrate the importance of validating crop simulation models across the range of intended treatments. (C) 2013 Elsevier E.V. All rights reserved.

Studies on Plant Demography: Ranunculus Repens L., R. Bulbosus L. and R. Acris L.: III. A Mathematical Model Incorporating Multiple Modes of Reproduction

This paper presents a comparative population dynamics study of three closely related species of buttercups (Ranunculus repens, R. acris, and R. bulbosus). The study is based on an investigation of the behaviour of the seeds in soil under field conditions and a continuous monitoring of survival and reproduction of some 9000 individual plants over a period of 21/2 years in a coastal grassland in North Wales. The data were analysed with the help of an extension of Leslie's matrix method which makes possible an simultaneous treatment of vegetative and sexual reproduction. It was found that R. repens (a) depends more heavily on vegetative as compared with sexual reproduction, (b) shows indications of negatively density-dependent population regulation, and (c) exhibits little variation in population growth rates from site to site and from one year to the next. In contrast, R. bulbosus (a) depends exclusively on sexual reproduction, (b) shows indications of a positively density-dependent population behaviour, and (c) exhibits great variation in population growth rates from site to site and from one year to the next. R. acris exhibits an intermediate behaviour in all these respects. It is suggested that the attributes of R. repens are those expected of a species inhabiting a stable environment, while R. bulbosus exhibits some of the characteristics of a fugitive species.

Using Bayesian networks to model surveillance in complex plant and animal health systems

In this chapter we consider biosecurity surveillance as part of a complex system comprising many different biological, environmental and human factors and their interactions. Modelling and analysis of surveillance strategies should take into account these complexities, and also facilitate the use and integration of the many types of different information that can provide insight into the system as a whole. After a brief discussion of a range of options, we focus on Bayesian networks for representing such complex systems. We summarize the features of Bayesian networks and describe these in the context of surveillance.