Part 1 MOO methods for multidisciplinary design using parallel evolutionary algorithms, game theory and hierarchical topology. (Part 1.) Theoretical aspects

Two lecture notes describe recent developments of evolutionary multi objective optimization (MO) techniques in detail and their advantages and drawbacks compared to traditional deterministic optimisers. The role of Game Strategies (GS), such as Pareto, Nash or Stackelberg games as companions or pre-conditioners of Multi objective Optimizers is presented and discussed on simple mathematical functions in Part I , as well as their implementations on simple aeronautical model optimisation problems on the computer using a friendly design framework in Part II. Real life (robust) design applications dealing with UAVs systems or Civil Aircraft and using the EAs and Game Strategies combined material of Part I & Part II are solved and discussed in Part III providing the designer new compromised solutions useful to digital aircraft design and manufacturing. Many details related to Lectures notes Part I, Part II and Part III can be found by the reader in [68].

How much information can be obtained from tracking the position of the leading edge in a scratch assay?

Moving cell fronts are an essential feature of wound healing, development and disease. The rate at which a cell front moves is driven, in part, by the cell motility, quantified in terms of the cell diffusivity $D$, and the cell proliferation rate �$\lambda$. Scratch assays are a commonly-reported procedure used to investigate the motion of cell fronts where an initial cell monolayer is scratched and the motion of the front is monitored over a short period of time, often less than 24 hours. The simplest way of quantifying a scratch assay is to monitor the progression of the leading edge. Leading edge data is very convenient since, unlike other methods, it is nondestructive and does not require labeling, tracking or counting individual cells amongst the population. In this work we study short time leading edge data in a scratch assay using a discrete mathematical model and automated image analysis with the aim of investigating whether such data allows us to reliably identify $D$ and $\lambda$�. Using a naıve calibration approach where we simply scan the relevant region of the ($D$;$\lambda$�) parameter space, we show that there are many choices of $D$ and $\lambda$� for which our model produces indistinguishable short time leading edge data. Therefore, without due care, it is impossible to estimate $D$ and $\lambda$� from this kind of data. To address this, we present a modified approach accounting for the fact that cell motility occurs over a much shorter time scale than proliferation. Using this information we divide the duration of the experiment into two periods, and we estimate $D$ using data from the first period, while we estimate �$\lambda$ using data from the second period. We confirm the accuracy of our approach using in silico data and a new set of in vitro data, which shows that our method recovers estimates of $D$ and $\lamdba$� that are consistent with previously-reported values except that that our approach is fast, inexpensive, nondestructive and avoids the need for cell labeling and cell counting.

Using ambient ozone for assignment of double bond position in unsaturated lipids

Unsaturated lipids deposited onto a range of materials are observed to react with the low concentrations of ozone present in normal laboratory air. Parent lipids and ozonolysis cleavage products are both detected directly from surfaces by desorption electrospray ionisation mass spectrometry (DESI-MS) with the resulting mass spectra providing clear evidence of the double bond position within these molecules. This serendipitous process has been coupled with thin-layer chromatography (TLC) to provide a simple but powerful approach for the detailed structural elucidation of lipids present in complex biological extracts. Lipid extracts from human lens were deposited onto normal phase TLC plates and then developed to separate components according to lipid class. Exposure of the developed plates to laboratory air for ca. 1 h prior to DESI-MS analysis gave rise to ozonolysis products allowing for the unambiguous identification of double bond positions in even low abundant, unsaturated lipids. In particular, the co-localization of intact unsaturated lactosylceramides (LacCer) with products from their oxidative cleavage provide the first evidence for the presence of three isomeric LacCer (d18:0/24:1) species in the ocular lens lipidome, i.e., variants with double bonds at the n-9, n-7 and n-5 positions.

A multi-hierarchical motorway ramp signalling strategy

Ramp signalling is an access control for motorways, in which a traffic signal is placed at on-ramps to regulate the rate of vehicles entering the motorway and thus to preserve the motorway capacity. In general, ramp signalling algorithms fall into two categories: local control and coordinated control by their effective scope. Coordinated ramp signalling strategies make use of measurements from the entire motorway network to operate individual ramp signals for the optimal performances at the network level. This study proposes a multi-hierarchical strategy for coordinated ramp signalling. The strategy is structured in two layers. At the higher layer with a longer update interval, coordination group is assembled and disassembled based on the location of high-risk breakdown flow. At the lower layer with a shorter update interval, individual ramps are hired to serve the coordination and are also released based on the prevailing congestion level on the ramp. This strategy is modelled and applied to the northbound Pacific Motorway micro-simulation platform (AIMSUN). The simulation results show an effective congestion mitigation of the proposed strategy.

Teaching and assessing ethics and social responsibility in undergraduate science : a position paper

Institutional graduate capabilities and discipline threshold learning outcomes require science students to demonstrate ethical conduct and social responsibility. However, neither the teaching nor the assessment of these concepts is straightforward. Australian chemistry academics participated in a workshop in 2013 to discuss and develop teaching and assessment in these areas and this paper reports on the outcomes of that workshop. Controversial issues discussed included: How broad is the mandate of the teacher, how should the boundaries between personal values and ethics be drawn, and how can ethics be assessed without moral judgement? In this position paper, I argue for a deep engagement with ethics and social justice, achieved through case studies and assessed against criteria that require discussion and debate. Strategies to effectively assess science students’ understanding of ethics and social responsibility are detailed.

Identification of double bond position in lipids : From GC to OzID

Recent developments in mass spectrometry and chromatography provide new possibilities for the identification and in some instances quantification of a wide range of lipids in complex matrices. These advances in analytical technologies have provided a tantalizing glimpse of the true structural diversity of lipids in nature and have reinvigorated interest in the role of lipids in biology. While technological advances have been impressive, difficulties in the ready identification of sites of unsaturation (i.e., double bond position) within these molecules presents a significant impediment to understanding lipid biochemistry. This is of particular importance given the growing body of literature suggesting that the presence of naturally occurring lipid double bond isomers can have a significant influence, both positive and negative, on the development of pathologies such as cancer, cardiovascular disease and type 2 diabetes. This article provides a critical review of the Current suite of analytical approaches to the challenge of identification of the position of carbon-carbon double bonds in intact lipids. Crown Copyright (C) 2009 Published by Elsevier B.V. All rights reserved.

Modeling and position-sensorless control of a dual-airgap axial flux permanent magnet machine for flywheel energy storage systems

This paper presents the modeling and position-sensorless vector control of a dual-airgap axial flux permanent magnet (AFPM) machine optimized for use in flywheel energy storage system (FESS) applications. The proposed AFPM machine has two sets of three-phase stator windings but requires only a single power converter to control both the electromagnetic torque and the axial levitation force. The proper controllability of the latter is crucial as it can be utilized to minimize the vertical bearing stress to improve the efficiency of the FESS. The method for controlling both the speed and axial displacement of the machine is discussed. An inherent speed sensorless observer is also proposed for speed estimation. The proposed observer eliminates the rotary encoder, which in turn reduces the overall weight and cost of the system while improving its reliability. The effectiveness of the proposed control scheme has been verified by simulations and experiments on a prototype machine.

Control of dense carbon nanotube arrays via hierarchical multilayer catalyst

Effective control of dense, high-quality carbon nanotube arrays using hierarchical multilayer catalyst patterns is demonstrated. Scanning/transmission electron microscopy, atomic force microscopy, Raman spectroscopy, and numerical simulations show that by changing the secondary and tertiary layers one can control the properties of the nanotube arrays. The arrays with the highest surface density of vertically aligned nanotubes are produced using a hierarchical stack of iron nanoparticles and alumina and silica layers differing in thickness by one order of magnitude from one another. The results are explained in terms of the catalyst structure effect on carbon diffusivity.

Hierarchical multilevel arrays of self-assembled gold nanoparticles : Control of resistivity-temperature dependence

The possibility to control the electric resistivity-temperature dependence of the nanosized resistive components made using hierarchical multilevel arrays of self-assembled gold nanoparticles prepared by multiple deposition/annealing is demonstrated. It is experimentally shown that the hierarchical three-level patterns, where the nanoparticles of sizes ranging from several nanometers to several tens of nanometer play a competitive roles in the electric conductivity, demonstrate sharp changes in the activation energy. These patterns can be used for the precise tuning of the resistivity-temperature behavior of nanoelectronic components.

Part 2. MOO methods for multidisciplinary design using parallel evolutionary algorithms, game theory and hierarchical topology. (Part 2.) Numerical aspects and implementation of model test cases

These lecture notes describe the use and implementation of a framework in which mathematical as well as engineering optimisation problems can be analysed. The foundations of the framework and algorithms described -Hierarchical Asynchronous Parallel Evolutionary Algorithms (HAPEAs) - lie upon traditional evolution strategies and incorporate the concepts of a multi-objective optimisation, hierarchical topology, asynchronous evaluation of candidate solutions , parallel computing and game strategies. In a step by step approach, the numerical implementation of EAs and HAPEAs for solving multi criteria optimisation problems is conducted providing the reader with the knowledge to reproduce these hand on training in his – her- academic or industrial environment.

Part 3. MOO methods for multidisciplinary design using parallel evolutionary algorithms, game theory and hierarchical topology. (Part 3.) Practical application to the design and optimisation of UAV systems

These lecture notes highlight some of the recent applications of multi-objective and multidisciplinary design optimisation in aeronautical design using the framework and methodology described in References 8, 23, 24 and in Part 1 and 2 of the notes. A summary of the methodology is described and the treatment of uncertainties in flight conditions parameters by the HAPEAs software and game strategies is introduced. Several test cases dealing with detailed design and computed with the software are presented and results discussed in section 4 of these notes.

Close-quarters Quadrotor flying for a pole inspection with position based visual servoing and high-speed vision

This paper presents a 100 Hz monocular position based visual servoing system to control a quadrotor flying in close proximity to vertical structures approximating a narrow, locally linear shape. Assuming the object boundaries are represented by parallel vertical lines in the image, detection and tracking is achieved using Plücker line representation and a line tracker. The visual information is fused with IMU data in an EKF framework to provide fast and accurate state estimation. A nested control design provides position and velocity control with respect to the object. Our approach is aimed at high performance on-board control for applications allowing only small error margins and without a motion capture system, as required for real world infrastructure inspection. Simulated and ground-truthed experimental results are presented.

A hierarchical model of goal directed navigation selects trajectories in a visual environment

We have developed a Hierarchical Look-Ahead Trajectory Model (HiLAM) that incorporates the firing pattern of medial entorhinal grid cells in a planning circuit that includes interactions with hippocampus and prefrontal cortex. We show the model’s flexibility in representing large real world environments using odometry information obtained from challenging video sequences. We acquire the visual data from a camera mounted on a small tele-operated vehicle. The camera has a panoramic field of view with its focal point approximately 5 cm above the ground level, similar to what would be expected from a rat’s point of view. Using established algorithms for calculating perceptual speed from the apparent rate of visual change over time, we generate raw dead reckoning information which loses spatial fidelity over time due to error accumulation. We rectify the loss of fidelity by exploiting the loop-closure detection ability of a biologically inspired, robot navigation model termed RatSLAM. The rectified motion information serves as a velocity input to the HiLAM to encode the environment in the form of grid cell and place cell maps. Finally, we show goal directed path planning results of HiLAM in two different environments, an indoor square maze used in rodent experiments and an outdoor arena more than two orders of magnitude larger than the indoor maze. Together these results bridge for the first time the gap between higher fidelity bio-inspired navigation models (HiLAM) and more abstracted but highly functional bio-inspired robotic mapping systems (RatSLAM), and move from simulated environments into real-world studies in rodent-sized arenas and beyond.

Bayesian hierarchical models for analysing spatial point-based data at a grid level: A comparison of approaches

Spatial data are now prevalent in a wide range of fields including environmental and health science. This has led to the development of a range of approaches for analysing patterns in these data. In this paper, we compare several Bayesian hierarchical models for analysing point-based data based on the discretization of the study region, resulting in grid-based spatial data. The approaches considered include two parametric models and a semiparametric model. We highlight the methodology and computation for each approach. Two simulation studies are undertaken to compare the performance of these models for various structures of simulated point-based data which resemble environmental data. A case study of a real dataset is also conducted to demonstrate a practical application of the modelling approaches. Goodness-of-fit statistics are computed to compare estimates of the intensity functions. The deviance information criterion is also considered as an alternative model evaluation criterion. The results suggest that the adaptive Gaussian Markov random field model performs well for highly sparse point-based data where there are large variations or clustering across the space; whereas the discretized log Gaussian Cox process produces good fit in dense and clustered point-based data. One should generally consider the nature and structure of the point-based data in order to choose the appropriate method in modelling a discretized spatial point-based data.

Rescaling clustering trees using impact ratios for robust hierarchical speaker clustering

We present a novel method for improving hierarchical speaker clustering in the tasks of speaker diarization and speaker linking. In hierarchical clustering, a tree can be formed that demonstrates various levels of clustering. We propose a ratio that expresses the impact of each cluster on the formation of this tree and use this to rescale cluster scores. This provides score normalisation based on the impact of each cluster. We use a state-of-the-art speaker diarization and linking system across the SAIVT-BNEWS corpus to show that our proposed impact ratio can provide a relative improvement of 16% in diarization error rate (DER).