A multiscale road map of cancer spheroids : incorporating experimental and mathematical modelling to understand cancer progression

Computational models represent a highly suitable framework, not only for testing biological hypotheses and generating new ones but also for optimising experimental strategies. As one surveys the literature devoted to cancer modelling, it is obvious that immense progress has been made in applying simulation techniques to the study of cancer biology, although the full impact has yet to be realised. For example, there are excellent models to describe cancer incidence rates or factors for early disease detection, but these predictions are unable to explain the functional and molecular changes that are associated with tumour progression. In addition, it is crucial that interactions between mechanical effects, and intracellular and intercellular signalling are incorporated in order to understand cancer growth, its interaction with the extracellular microenvironment and invasion of secondary sites. There is a compelling need to tailor new, physiologically relevant in silico models that are specialised for particular types of cancer, such as ovarian cancer owing to its unique route of metastasis, which are capable of investigating anti-cancer therapies, and generating both qualitative and quantitative predictions. This Commentary will focus on how computational simulation approaches can advance our understanding of ovarian cancer progression and treatment, in particular, with the help of multicellular cancer spheroids, and thus, can inform biological hypothesis and experimental design.

CFD and experimental modelling of an impinging jet for thunderstorm downburst simulation

A thunderstorm downburst in its simplest form can be modelled as a steady flow impinging air jet. Although this simplification neglects some important atmospheric and physical parameters it has proven to be a useful tool for understanding the kinematics of these events. Assuming this simple impinging jet model also allows numerical models to be developed which can be directly compared with experimental results to validate the use of CFD. Confidence gained from these simulations will allow the use of more complex atmospheric impinging jet models that cannot be directly validated. Thunderstorm downbursts are important for wind engineers because in many parts of the world they produce the design wind speeds used in design standards, but are not structurally represented in these documents.

A framework for model integration and holistic modelling of socio-technical systems

This paper presents a layered framework for the purposes of integrating different Socio-Technical Systems (STS) models and perspectives into a whole-of-systems model. Holistic modelling plays a critical role in the engineering of STS due to the interplay between social and technical elements within these systems and resulting emergent behaviour. The framework decomposes STS models into components, where each component is either a static object, dynamic object or behavioural object. Based on existing literature, a classification of the different elements that make up STS, whether it be a social, technical or a natural environment element, is developed; each object can in turn be classified according to the STS elements it represents. Using the proposed framework, it is possible to systematically decompose models to an extent such that points of interface can be identified and the contextual factors required in transforming the component of one model to interface into another is obtained. Using an airport inbound passenger facilitation process as a case study socio-technical system, three different models are analysed: a Business Process Modelling Notation (BPMN) model, Hybrid Queue-based Bayesian Network (HQBN) model and an Agent Based Model (ABM). It is found that the framework enables the modeller to identify non-trivial interface points such as between the spatial interactions of an ABM and the causal reasoning of a HQBN, and between the process activity representation of a BPMN and simulated behavioural performance in a HQBN. Such a framework is a necessary enabler in order to integrate different modelling approaches in understanding and managing STS.

Nanoscale studies of materials using x-ray synchrotron radiation and mesoscopic modelling

X-ray synchrotron radiation was used to study the nanostructure of cellulose in Norway spruce stem wood and powders of cobalt nanoparticles in cellulose support. Furthermore, the growth of metallic clusters was modelled and simulated in the mesoscopic size scale. Norway spruce was characterized with x-ray microanalysis at beamline ID18F of the European Synchrotron Radiation Facility in Grenoble. The average dimensions and the orientation of cellulose crystallites was determined using x-ray microdiffraction. In addition, the nutrient element content was determined using x-ray fluorescence spectroscopy. Diffraction patterns and fluorescence spectra were simultaneously acquired. Cobalt nanoparticles in cellulose support were characterized with x-ray absorption spectroscopy at beamline X1 of the Deutsches Elektronen-Synchrotron in Hamburg, complemented by home lab experiments including x-ray diffraction, electron microscopy and measurement of magnetic properties with a vibrating sample magnetometer. Extended x-ray absorption fine structure spectroscopy (EXAFS) and x-ray diffraction were used to solve the atomic arrangement of the cobalt nanoparticles. Scanning- and transmission electron microscopy were used to image the surfaces of the cellulose fibrils, where the growth of nanoparticles takes place. The EXAFS experiment was complemented by computational coordination number calculations on ideal spherical nanocrystals. The growth process of metallic nanoclusters on cellulose matrix is assumed to be rather complicated, affected not only by the properties of the clusters themselves, but essentially depending on the cluster-fiber interfaces as well as the morphology of the fiber surfaces. The final favored average size for nanoclusters, if such exists, is most probably a consequence of these two competing tendencies towards size selection, one governed by pore sizes, the other by the cluster properties. In this thesis, a mesoscopic model for the growth of metallic nanoclusters on porous cellulose fiber (or inorganic) surfaces is developed. The first step in modelling was to evaluate the special case of how the growth proceeds on flat or wedged surfaces.

Computational modeling and psychophysics in low- and mid-level vision

This thesis addresses a series of topics related to the question of how people find the foreground objects from complex scenes. With both computer vision modeling, as well as psychophysical analyses, we explore the computational principles for low- and mid-level vision.

We first explore the computational methods of generating saliency maps from images and image sequences. We propose an extremely fast algorithm called Image Signature that detects the locations in the image that attract human eye gazes. With a series of experimental validations based on human behavioral data collected from various psychophysical experiments, we conclude that the Image Signature and its spatial-temporal extension, the Phase Discrepancy, are among the most accurate algorithms for saliency detection under various conditions.

In the second part, we bridge the gap between fixation prediction and salient object segmentation with two efforts. First, we propose a new dataset that contains both fixation and object segmentation information. By simultaneously presenting the two types of human data in the same dataset, we are able to analyze their intrinsic connection, as well as understanding the drawbacks of today’s “standard” but inappropriately labeled salient object segmentation dataset. Second, we also propose an algorithm of salient object segmentation. Based on our novel discoveries on the connections of fixation data and salient object segmentation data, our model significantly outperforms all existing models on all 3 datasets with large margins.

In the third part of the thesis, we discuss topics around the human factors of boundary analysis. Closely related to salient object segmentation, boundary analysis focuses on delimiting the local contours of an object. We identify the potential pitfalls of algorithm evaluation for the problem of boundary detection. Our analysis indicates that today’s popular boundary detection datasets contain significant level of noise, which may severely influence the benchmarking results. To give further insights on the labeling process, we propose a model to characterize the principles of the human factors during the labeling process.

The analyses reported in this thesis offer new perspectives to a series of interrelating issues in low- and mid-level vision. It gives warning signs to some of today’s “standard” procedures, while proposing new directions to encourage future research.

Effects of flow geometry and Damkohler number on turbulent premixed flame

DNS of planar turbulent flame and turbulent V-flame has been conducted to investigate turbulence-scalar interaction in relatively practical turbulent combustion. Several turbulence quantities are examined for the understandings of fundamental characteristics of flow field in V-flame. Due to the additional turbulence production by the hot-rod, turbulence does not simply decay in V-flame. Turbulence-scalar interaction, scalar alignments with the principal strain rate in other words, is then clarified. The competition of turbulence and dilatation can be found in the conditional PDF of flame normal alignment. The results suggests that the alignment characteristics in high Da flames are applicable to low Da flames in the region of intense heat release.

High dimensional imagery geometry and it's applications

Because of information digitalization and the correspondence of digits and the coordinates, Information Science and high-dimensional space have consanguineous relations. With the transforming from the information issues to the point analysis in high-dimensional space, we proposed a novel computational theory, named High dimensional imagery geometry (HDIG). Some computational algorithms of HDIG have been realized using software, and how to combine with groups of simple operators in some 2D planes to implement the geometrical computations in high-dimensional space is demonstrated in this paper. As the applications, two kinds of experiments of HDIG, which are blurred image restoration and pattern recognition ones, are given, and the results are satisfying.

Computational issues in the modelling of materials-based manufacturing processes

The manufacture of materials products involves the control of a range of interacting physical phenomena. The material to be used is synthesised and then manipulated into some component form. The structure and properties of the final component are influenced by both interactions of continuum-scale phenomena and those at an atomistic-scale level. Moreover, during the processing phase there are some properties that cannot be measured (typically the liquid-solid phase change). However, it seems there is a potential to derive properties and other features from atomistic-scale simulations that are of key importance at the continuum scale. Some of the issues that need to be resolved in this context focus upon computational techniques and software tools facilitating: (i) the multiphysics modeling at continuum scale; (ii) the interaction and appropriate degrees of coupling between the atomistic through microstructure to continuum scale; and (iii) the exploitation of high-performance parallel computing power delivering simulation results in a practical time period. This paper discusses some of the attempts to address each of the above issues, particularly in the context of materials processing for manufacture.

Integration Of Strength and Process Modelling of Friction-Stir-Welded Fuselage Panels

In order to reduce potential uncertainties and conservatism in welded panel analysis procedures, understanding of the relationships between welding process parameters and static strength is required. The aim of this study is to determine and characterize the key process induced properties of advanced welding assembly methods on stiffened panel local buckling and collapse performance. To this end, an in-depth experimental and computational study of the static strength of a friction stir welded fuselage skin-stiffener panel subjected to compression loading has been undertaken. Four welding process effects, viz. the weld joint width, the width of the weld Heat Affected Zone, the strength of material within the weld Heat Affected Zone and the magnitude of welding induced residual stress, are investigated. A fractional factorial experiment design method (Taguchi) has been applied to identify the relative importance of each welding process effect and investigate effect interactions on both local skin buckling and crippling collapse performance. For the identified dominant welding process effects, parametric studies have been undertaken to identify critical welding process effect magnitudes and boundaries. The studies have shown that local skin buckling is principally influenced by the magnitude of welding induced residual stress and that the strength of material in the Heat Affected Zone and the magnitude of the welding induced residual stress have the greatest influence on crippling collapse behavior.


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Computational Models of Object Recognition in Cortex: A Review

Understanding how biological visual systems perform object recognition is one of the ultimate goals in computational neuroscience. Among the biological models of recognition the main distinctions are between feedforward and feedback and between object-centered and view-centered. From a computational viewpoint the different recognition tasks - for instance categorization and identification - are very similar, representing different trade-offs between specificity and invariance. Thus the different tasks do not strictly require different classes of models. The focus of the review is on feedforward, view-based models that are supported by psychophysical and physiological data.

Stimulus Simplification and Object Representation: A Modeling Study

Tsunoda et al. (2001) recently studied the nature of object representation in monkey inferotemporal cortex using a combination of optical imaging and extracellular recordings. In particular, they examined IT neuron responses to complex natural objects and "simplified" versions thereof. In that study, in 42% of the cases, optical imaging revealed a decrease in the number of activation patches in IT as stimuli were "simplified". However, in 58% of the cases, "simplification" of the stimuli actually led to the appearance of additional activation patches in IT. Based on these results, the authors propose a scheme in which an object is represented by combinations of active and inactive columns coding for individual features. We examine the patterns of activation caused by the same stimuli as used by Tsunoda et al. in our model of object recognition in cortex (Riesenhuber 99). We find that object-tuned units can show a pattern of appearance and disappearance of features identical to the experiment. Thus, the data of Tsunoda et al. appear to be in quantitative agreement with a simple object-based representation in which an object's identity is coded by its similarities to reference objects. Moreover, the agreement of simulations and experiment suggests that the simplification procedure used by Tsunoda (2001) is not necessarily an accurate method to determine neuronal tuning.

On lions, impala, and bigraphs: modelling interactions in Ubiquitous Computing

As ubiquitous systems have moved out of the lab and into the world the need to think more systematically about how there are realised has grown. This talk will present intradisciplinary work I have been engaged in with other computing colleagues on how we might develop more formal models and understanding of ubiquitous computing systems. The formal modelling of computing systems has proved valuable in areas as diverse as reliability, security and robustness. However, the emergence of ubiquitous computing raises new challenges for formal modelling due to their contextual nature and dependence on unreliable sensing systems. In this work we undertook an exploration of modelling an example ubiquitous system called the Savannah game using the approach of bigraphical rewriting systems. This required an unusual intra-disciplinary dialogue between formal computing and human- computer interaction researchers to model systematically four perspectives on Savannah: computational, physical, human and technical. Each perspective in turn drew upon a range of different modelling traditions. For example, the human perspective built upon previous work on proxemics, which uses physical distance as a means to understand interaction. In this talk I hope to show how our model explains observed inconsistencies in Savannah and ex- tend it to resolve these. I will then reflect on the need for intradisciplinary work of this form and the importance of the bigraph diagrammatic form to support this form of engagement. Speaker Biography Tom Rodden Tom Rodden (rodden.info) is a Professor of Interactive Computing at the University of Nottingham. His research brings together a range of human and technical disciplines, technologies and techniques to tackle the human, social, ethical and technical challenges involved in ubiquitous computing and the increasing used of personal data. He leads the Mixed Reality Laboratory (www.mrl.nott.ac.uk) an interdisciplinary research facility that is home of a team of over 40 researchers. He founded and currently co-directs the Horizon Digital Economy Research Institute (www.horizon.ac.uk), a university wide interdisciplinary research centre focusing on ethical use of our growing digital footprint. He has previously directed the EPSRC Equator IRC (www.equator.ac.uk) a national interdisciplinary research collaboration exploring the place of digital interaction in our everyday world. He is a fellow of the British Computer Society and the ACM and was elected to the ACM SIGCHI Academy in 2009 (http://www.sigchi.org/about/awards/).

A parametric approach to 3D massing and density modelling

This paper addresses the current void between social agendas, environmental criteria and design methodology in urban planning through the implementation of new computational systems. It considers the application of digital design tools such as GIS and parametric systems towards more efficient and effective design solutions. The digital design methods have been developed and tested within Grimshaw Architects Design Technology Group on both Australian and international urban development projects. A methodology for the use of parametric design for urban design development is suggested for defining, simplifying and categorising planning and design strategies. The following tools are a means of generating urban design concepts as digital forms in order to better inform the designer during the design process.

Electrothermal characterization and nonlinear modelling of GaN transistors for telecommunication circuit design

This thesis starts showing the main characteristics and application fields of the AlGaN/GaN HEMT technology, focusing on reliability aspects essentially due to the presence of low frequency dispersive phenomena which limit in several ways the microwave performance of this kind of devices. Based on an equivalent voltage approach, a new low frequency device model is presented where the dynamic nonlinearity of the trapping effect is taken into account for the first time allowing considerable improvements in the prediction of very important quantities for the design of power amplifier such as power added efficiency, dissipated power and internal device temperature. An innovative and low-cost measurement setup for the characterization of the device under low-frequency large-amplitude sinusoidal excitation is also presented. This setup allows the identification of the new low frequency model through suitable procedures explained in detail. In this thesis a new non-invasive empirical method for compact electrothermal modeling and thermal resistance extraction is also described. The new contribution of the proposed approach concerns the non linear dependence of the channel temperature on the dissipated power. This is very important for GaN devices since they are capable of operating at relatively high temperatures with high power densities and the dependence of the thermal resistance on the temperature is quite relevant. Finally a novel method for the device thermal simulation is investigated: based on the analytical solution of the tree-dimensional heat equation, a Visual Basic program has been developed to estimate, in real time, the temperature distribution on the hottest surface of planar multilayer structures. The developed solver is particularly useful for peak temperature estimation at the design stage when critical decisions about circuit design and packaging have to be made. It facilitates the layout optimization and reliability improvement, allowing the correct choice of the device geometry and configuration to achieve the best possible thermal performance.