Experimental arts practice incorporating motion capture

My practice-led research explores and maps workflows for generating experimental creative work involving inertia based motion capture technology. Motion capture has often been used as a way to bridge animation and dance resulting in abstracted visuals outcomes. In early works this process was largely done by rotoscoping, reference footage and mechanical forms of motion capture. With the evolution of technology, optical and inertial forms of motion capture are now more accessible and able to accurately capture a larger range of complex movements. Made by Motion is a collaboration between digital artist Paul Van Opdenbosch and performer and choreographer Elise May; a series of studies on captured motion data used to generate experimental visual forms that reverberate in space and time. The project investigates the invisible forces generated by and influencing the movement of a dancer. Along with how the forces can be captured and applied to generating visual outcomes that surpass simple data visualisation, projecting the intent of the performer’s movements. The source or ‘seed’ comes from using an Xsens MVN – Inertial Motion Capture system to capture spontaneous dance movements, with the visual generation conducted through a customised dynamics simulation. In my presentation I will be displaying and discussing a selected creative works from the project along with the process and considerations behind the work.

Continuous remote emissions monitoring – the lynchpin for air quality management

Diesel particulate matter (DPM), in particular, has been likened in a somewhat inflammatory manner to be the ‘next asbestos’. From the business change perspective, there are three areas holding the industry back from fully engaging with the issue: 1. There is no real feedback loop in any operational sense to assess the impact of investment or application of controls to manage diesel emissions. 2. DPM are getting ever smaller and more numerous, but there is no practical way of measuring them to regulate them in the field. Mass, the current basis of regulation, is becoming less and less relevant. 3. Diesel emissions management is generally wholly viewed as a cost, yet there are significant areas of benefit available from good management. This paper discusses a feedback approach to address these three areas to move the industry forward. The six main areas of benefit from providing a feedback loop by continuously monitoring diesel emissions have been identified: 1. Condition-based maintenance. Emissions change instantaneously if engine condition changes. 2. Operator performance. An operator can use a lot more fuel for little incremental work output through poor technique or discipline. 3. Vehicle utilisation. Operating hours achieved and ratios of idling to under power affect the proportion of emissions produced with no economic value. 4. Fuel efficiency. This allows visibility into other contributing configuration and environmental factors for the vehicle. 5. Emission rates. This allows scope to directly address the required ratio of ventilation to diesel emissions. 6. Total carbon emissions - for NGER-type reporting requirements, calculating the emissions individually from each vehicle rather than just reporting on fuel delivered to a site.

Design of physiological control and magnetic levitation systems for a total artificial heart

Total Artificial Hearts are mechanical pumps which can be used to replace the failing natural heart. This novel study developed a means of controlling a new design of pump to reproduce physiological flow bringing closer the realisation of a practical artificial heart. Using a mathematical model of the device, an optimisation algorithm was used to determine the best configuration for the magnetic levitation system of the pump. The prototype device was constructed and tested in a mock circulation loop. A physiological controller was designed to replicate the Frank-Starling like balancing behaviour of the natural heart. The device and controller provided sufficient support for a human patient while also demonstrating good response to various physiological conditions and events. This novel work brings the design of a practical artificial heart closer to realisation.

Hairpin RNAs derived from RNA polymerase II and polymerase III promoter-directed transgenes are processed differently in plants

RNA polymerase III (Pol III) as well as Pol II (35S) promoters are able to drive hairpin RNA (hpRNA) expression and induce target gene silencing in plants. siRNAs of 21 nt are the predominant species in a 35S Pol II line, whereas 24- and/or 22-nucleotide (nt) siRNAs are produced by a Pol III line. The 35S line accumulated the loop of the hpRNA, in contrast to full-length hpRNA in the Pol III line. These suggest that Pol II and Pol III-transcribed hpRNAs are processed by different pathways. One Pol III transgene produced only 24-nt siRNAs but silenced the target gene efficiently, indicating that the 24-nt siRNAs can direct mRNA degradation; specific cleavage was confirmed by 59 rapid amplification of cDNA ends (RACE). Both Pol II- and Pol III-directed hpRNA transgenes induced cytosine methylation in the target DNA. The extent of methylation is not correlated with the level of 21-nt siRNAs, suggesting that they are not effective inducers of DNA methylation. The promoter of a U6 transgene was significantly methylated, whereas the promoter of the endogenous U6 gene was almost free of cytosine methylation, suggesting that endogenous sequences are more resistant to de novo DNA methylation than are transgene constructs. Published by Cold Spring Harbor Laboratory Press. Copyright © 2008 RNA Society.

The use of artificial MicroRNA technology to control gene expression in Arabidopsis thaliana

In plants, double-stranded RNA (dsRNA) is an effective trigger of RNA silencing, and several classes of endogenous small RNA (sRNA), processed from dsRNA substrates by DICER-like (DCL) endonucleases, are essential in controlling gene expression. One such sRNA class, the microRNAs (miRNAs) control the expression of closely related genes to regulate all aspects of plant development, including the determination of leaf shape, leaf polarity, flowering time, and floral identity. A single miRNA sRNA silencing signal is processed from a long precursor transcript of nonprotein-coding RNA, termed the primary miRNA (pri-miRNA). A region of the pri-miRNA is partially self-complementary allowing the transcript to fold back onto itself to form a stem-loop structure of imperfectly dsRNA. Artificial miRNA (amiRNA) technology uses endogenous pri-miRNAs, in which the miRNA and miRNA*(passenger strand of the miRNA duplex) sequences have been replaced with corresponding amiRNA/ amiRNA*sequences that direct highly efficient RNA silencing of the targeted gene. Here, we describe the rules for amiRNA design, as well as outline the PCR and bacterial cloning procedures involved in the construction of an amiRNA plant expression vector to control target gene expression in Arabidopsis thaliana. © 2014 Springer Science+Business Media New York.

Efficient silencing of endogenous microRNAs using artificial microRNAs in Arabidopsis thaliana

We report here that the expression of endogenous microRNAs (miRNAs) can be efficiently silenced in Arabidopsis thaliana (Arabidopsis) using artificial miRNA (amiRNA) technology. We demonstrate that an amiRNA designed to target a mature miRNA directs silencing against all miRNA family members, whereas an amiRNA designed to target the stem-loop region of a miRNA precursor transcript directs silencing against only the individual family member targeted. Furthermore, our results indicate that amiRNAs targeting both the mature miRNA and stem-loop sequence direct RNA silencing through cleavage of the miRNA precursor transcript, which presumably occurs in the nucleus of a plant cell during the initial stages of miRNA biogenesis. This suggests that small RNA (sRNA)-guided RNA cleavage in plants occurs not only in the cytoplasm, but also in the nucleus. Many plant miRNA gene families have been identified via sequencing and bioinformatic analysis, but, to date, only a small tranche of these have been functionally characterized due to a lack of effective forward or reverse genetic tools. Our findings therefore provide a new and powerful reverse-genetic tool for the analysis of miRNA function in plants. © The Author 2010. Published by the Molecular Plant Shanghai Editorial Office in association with Oxford University Press on behalf of CSPP and IPPE, SIBS, CAS.

Cloning and characterization of microRNAs from Brassica napus

A library containing approximately 40,000 small RNA sequences was constructed for Brassica napus. Analysis of 3025 sequences obtained from this library resulted in the identification of 11 conserved miRNA families, which were validated by secondary structure prediction using surrounding sequences in the Brassica genome. Two 21 nt small RNA sequences reside within the arm of a pre-miRNA like stem-loop structure, making them likely candidates for novel non-conserved miRNAs in B. napus. Most of the conserved miRNAs were expressed at similar levels in a F1 hybrid B. napus line and its four double haploid progeny that showed marked variations in phenotypes, but many were differentially expressed between B. napus and Arabidopsis. The miR169 family was expressed at high levels in young leaves and stems, but was undetectable in roots and mature leaves, suggesting that miR169 expression is developmentally regulated in B. napus. © 2007 Federation of European Biochemical Societies.

Odometry-driven inference to link multiple exemplars of a location

A major challenge for robot localization and mapping systems is maintaining reliable operation in a changing environment. Vision-based systems in particular are susceptible to changes in illumination and weather, and the same location at another time of day may appear radically different to a system using a feature-based visual localization system. One approach for mapping changing environments is to create and maintain maps that contain multiple representations of each physical location in a topological framework or manifold. However, this requires the system to be able to correctly link two or more appearance representations to the same spatial location, even though the representations may appear quite dissimilar. This paper proposes a method of linking visual representations from the same location without requiring a visual match, thereby allowing vision-based localization systems to create multiple appearance representations of physical locations. The most likely position on the robot path is determined using particle filter methods based on dead reckoning data and recent visual loop closures. In order to avoid erroneous loop closures, the odometry-based inferences are only accepted when the inferred path's end point is confirmed as correct by the visual matching system. Algorithm performance is demonstrated using an indoor robot dataset and a large outdoor camera dataset.

A systemic view of innovation adoption in the Australian beef industry

Significant investments in developing technological innovations have been made in the Australian beef industry but with low adoption rates. By modelling the key variables and their interactions in the innovation adoption process, this research seeks to demonstrate the complexity and dynamics of the process. This research uses causal loop modelling and develops a holistic model of the current innovation adoption system in the Australian beef industry to show the complexity of dynamic interactions among multiple variables. It is suggested that innovation adoption is such an extremely complex issue, and we need to shift our views on this issue from a paradigm of linear thinking to systems thinking. Innovation adoption is more likely to be enhanced based on a full understanding of the complexity and dynamics of the system as a whole. The paper demonstrates to practitioners and developers of innovation the multiple variables and interactions impacting innovation adoption.

Hybrid model for motorway travel time estimation considering increased detector spacing

Travel time estimation and prediction on motorways has long been a topic of research. Prediction modeling generally assumes that the estimation is perfect. No matter how good is the prediction modeling- the errors in estimation can significantly deteriorate the accuracy and reliability of the prediction. Models have been proposed to estimate travel time from loop detector data. Generally, detectors are closely spaced (say 500m) and travel time can be estimated accurately. However, detectors are not always perfect, and even during normal running conditions few detectors malfunction, resulting in increase in the spacing between the functional detectors. Under such conditions, error in the travel time estimation is significantly large and generally unacceptable. This research evaluates the in-practice travel time estimation model during different traffic conditions. It is observed that the existing models fail to accurately estimate travel time during large detector spacing and congestion shoulder periods. Addressing this issue, an innovative Hybrid model that only considers loop data for travel time estimation is proposed. The model is tested using simulation and is validated with real Bluetooth data from Pacific Motorway Brisbane. Results indicate that during non free flow conditions and larger detector spacing Hybrid model provides significant improvement in the accuracy of travel time estimation.

RatSLAM : using models of rodent hippocampus for robot navigation and beyond

We describe recent biologically-inspired mapping research incorporating brain-based multi-sensor fusion and calibration processes and a new multi-scale, homogeneous mapping framework. We also review the interdisciplinary approach to the development of the RatSLAM robot mapping and navigation system over the past decade and discuss the insights gained from combining pragmatic modelling of biological processes with attempts to close the loop back to biology. Our aim is to encourage the pursuit of truly interdisciplinary approaches to robotics research by providing successful case studies.

Can we text you? A qualitative exploration of young unemployed job-seekers’ attitudes to receiving resilience-building SMS messages

A significant minority of young job-seekers remain unemployed for many months, and are at risk of developing depression. Both empirical studies and theoretical models suggest that cognitive, behavioural and social isolation factors interact to increase this risk. Thus, interventions that reduce or prevent depression in young unemployed job-seekers by boosting their resilience are required. Mobile phones may be an effective medium to deliver resilience-boosting support to young unemployed people by using SMS messages to interrupt the feedback loop of depression and social isolation. Three focus groups were conducted to explore young unemployed job-seekers’ attitudes to receiving and requesting regular SMS messages that would help them to feel supported and motivated while job-seeking. Participants reacted favourably to this proposal, and thought that it would be useful to continue to receive and request SMS messages for a few months after commencing employment as well.

Structures of μOconotoxins from Conusmarmoreus. Inhibitors of tetrodotoxin (TTX)-sensitive and TTX-resistant sodium channels in mammalian sensory neurons

The μO-conotoxins are an intriguing class of conotoxins targeting various voltage-dependent sodium channels and molluscan calcium channels. In the current study, we have shown MrVIA and MrVIB to be the first known peptidic inhibitors of the transient tetrodotoxin-resistant (TTX-R) Na+ current in rat dorsal root ganglion neurons, in addition to inhibiting tetrodotoxin-sensitive Na+ currents. Human TTX-R sodium channels are a therapeutic target for indications such as pain, highlighting the importance of the μO-conotoxins as potential leads for drug development. Furthermore, we have used NMR spectroscopy to provide the first structural information on this class of conotoxins. MrVIA and MrVIB are hydrophobic peptides that aggregate in aqueous solution but were solubilized in 50% acetonitrile/water. The three-dimensional structure of MrVIB consists of a small β-sheet and a cystine knot arrangement of the three-disulfide bonds. It contains four backbone “loops” between successive cysteine residues that are exposed to the solvent to varying degrees. The largest of these, loop 2, is the most disordered part of the molecule, most likely due to flexibility in solution. This disorder is the most striking difference between the structures of MrVIB and the known δ- and ω-conotoxins, which along with the μO-conotoxins are members of the O superfamily. Loop 2 of ω-conotoxins has previously been shown to contain residues critical for binding to voltage-gated calcium channels, and it is interesting to speculate that the flexibility observed in MrVIB may accommodate binding to both sodium and molluscan calcium channels.

Distribution harmonic state estimation based on a modified PSO considering parameters uncertainty

This paper presents a new algorithm based on a Modified Particle Swarm Optimization (MPSO) to estimate the harmonic state variables in a distribution networks. The proposed algorithm performs the estimation for both amplitude and phase of each injection harmonic currents by minimizing the error between the measured values from Phasor Measurement Units (PMUs) and the values computed from the estimated parameters during the estimation process. The proposed algorithm can take into account the uncertainty of the harmonic pseudo measurement and the tolerance in the line impedances of the network as well as the uncertainty of the Distributed Generators (DGs) such as Wind Turbines (WTs). The main features of the proposed MPSO algorithm are usage of a primary and secondary PSO loop and applying the mutation function. The simulation results on 34-bus IEEE radial and a 70-bus realistic radial test networks are presented. The results demonstrate that the speed and the accuracy of the proposed Distribution Harmonic State Estimation (DHSE) algorithm are very excellent compared to the algorithms such as Weight Least Square (WLS), Genetic Algorithm (GA), original PSO, and Honey Bees Mating Optimization (HBMO).

The mitochondrial genome of the Russian wheat aphid Diuraphis noxia : large repetitive sequences between trnE and trnF in aphids

To characterize aphid mitochondrial genome (mitogenome) features, we sequenced the complete mitogenome of the Russian wheat aphid, Diuraphis noxia. The 15,784-bp mitogenome with a high A + T content (84.76%) and strong C skew (− 0.26) was arranged in the same gene order as that of the ancestral insect. Unlike typical insect mitogenomes, D. noxia possessed a large tandem repeat region (644 bp) located between trnE and trnF. Sequencing partial mitogenome of the cotton aphid (Aphis gossypii) further confirmed the presence of the large repeat region in aphids, but with different repeat length and copy number. Another motif (58 bp) tandemly repeated 2.3 times in the control region of D. noxia. All repeat units in D. noxia could be folded into stem-loop secondary structures, which could further promote an increase in copy numbers. Characterization of the D. noxia mitogenome revealed distinct mitogenome architectures, thus advancing our understanding of insect mitogenomic diversities and evolution.