Design of redox/radical sensing molecules via Nitrile Imine-Mediated Tetrazole-ene Cycloaddition (NITEC)

The current study introduces a novel synthetic avenue for the preparation of profluorescent nitroxides via nitrile imine-mediated tetrazole-ene cycloaddition (NITEC). The photoinduced cycloaddition was performed under metal-free, mild conditions allowing the preparation of a library of the nitroxide functionalized pyrazolines and corresponding methoxyamines. High reaction rates and full conversion were observed, with the presence of the nitroxide having no significant impact on the cycloaddition performance. The formed products were investigated with respect to their photophysical properties in order to quantify their “switch on/off” behavior. The fluorescence quenching performance is strongly dependent on the distance between the chromophore and the free radical spin as demonstrated theoretically and experimentally. Highest levels of fluorescence quenching were achieved for pyrazolines with the nitroxide directly fused to the chromophore. Importantly, the pyrazoline profluorescent nitroxides were shown to efficiently act as sensors for redox/radical processes.

Collaborative data exploration interfaces - From participatory sensing to participatory sensemaking

As technological capabilities for capturing, aggregating, and processing large quantities of data continue to improve, the question becomes how to effectively utilise these resources. Whenever automatic methods fail, it is necessary to rely on human background knowledge, intuition, and deliberation. This creates demand for data exploration interfaces that support the analytical process, allowing users to absorb and derive knowledge from data. Such interfaces have historically been designed for experts. However, existing research has shown promise in involving a broader range of users that act as citizen scientists, placing high demands in terms of usability. Visualisation is one of the most effective analytical tools for humans to process abstract information. Our research focuses on the development of interfaces to support collaborative, community-led inquiry into data, which we refer to as Participatory Data Analytics. The development of data exploration interfaces to support independent investigations by local communities around topics of their interest presents a unique set of challenges, which we discuss in this paper. We present our preliminary work towards suitable high-level abstractions and interaction concepts to allow users to construct and tailor visualisations to their own needs.

Remote Sensing and Data Collection from Solar Powered Wireless Sensor Network using an Unmanned Aerial Vehicle System

Sensor networks for environmental monitoring present enormous benefits to the community and society as a whole. Currently there is a need for low cost, compact, solar powered sensors suitable for deployment in rural areas. The purpose of this research is to develop both a ground based wireless sensor network and data collection using unmanned aerial vehicles. The ground based sensor system is capable of measuring environmental data such as temperature or air quality using cost effective low power sensors. The sensor will be configured such that its data is stored on an ATMega16 microcontroller which will have the capability of communicating with a UAV flying overhead using UAV communication protocols. The data is then either sent to the ground in real time or stored on the UAV using a microcontroller until it lands or is close enough to enable the transmission of data to the ground station.

LiDAR Augmented Optimal Path Planning for Unmanned Aerial Vehicle during Remote Sensing at Low Altitude and Network Sensor Data Acquisition

This technical report describes a Light Detection and Ranging (LiDAR) augmented optimal path planning at low level flight methodology for remote sensing and sampling Unmanned Aerial Vehicles (UAV). The UAV is used to perform remote air sampling and data acquisition from a network of sensors on the ground. The data that contains information on the terrain is in the form of a 3D point clouds maps is processed by the algorithms to find an optimal path. The results show that the method and algorithm are able to use the LiDAR data to avoid obstacles when planning a path from a start to a target point. The report compares the performance of the method as the resolution of the LIDAR map is increased and when a Digital Elevation Model (DEM) is included. From a practical point of view, the optimal path plan is loaded and works seemingly with the UAV ground station and also shows the UAV ground station software augmented with more accurate LIDAR data.

Green Falcon and Raptor UAV for remote gas sensing

This report documents showcases my learning experiences and design of Green Falcon Solar Powered UAV. Only responsible aspects will be discussed inside this report. Using solar power that is captured by solar panels it can fly all day and also store power for night flying. Its major advantage lies in the fact that it is simple and versatile, which makes it applicable to a large range of UAVs of different wingspans. Green Falcon UAV is designed as a supporting tool for scientists to get a deeper understanding of gases exchange amongst ground plane and atmosphere

Processing and compressive strength of Al-Li-SiCp composites fabricated by a compound billet technique

Al-Li-SiCp composites were fabricated by a simple and cost effective stir casting technique. A compound billet technique has been developed to overcome the problems encountered during hot extrusion of these composites. After successful fabrication hardness measurement and room temperature compressive test were carried out on 8090 Al and its composites reinforced with 8, 12 and 18vol.% SiC particles in as extruded and peak aged conditions. The addition of SiC increases the hardness. 0.2% proof stress and compressive strength of Al-Li-8%SiC and Al-Li-12%SiC composites are higher than the unreinforced alloy. in case of the Al-Li-18%SiC composite, the 0.2% proof stress and compressive strength were higher than the unreinforced alloy but lower than those of Al-Li-8%SiC and Al-Li-12%SiC composites. This is attributed to clustering of particles and poor interfacial bonding.

Quasi-static and dynamic strain sensing using carbon nanotube/epoxy nanocomposite thin films

Thin films are developed by dispersing carbon black nanoparticles and carbon nanotubes (CNTs) in an epoxy polymer. The films show a large variation in electrical resistance when subjected to quasi-static and dynamic mechanical loading. This phenomenon is attributed to the change in the band-gap of the CNTs due to the applied strain, and also to the change in the volume fraction of the constituent phases in the percolation network. Under quasi-static loading, the films show a nonlinear response. This nonlinearity in the response of the films is primarily attributed to the pre-yield softening of the epoxy polymer. The electrical resistance of the films is found to be strongly dependent on the magnitude and frequency of the applied dynamic strain, induced by a piezoelectric substrate. Interestingly, the resistance variation is found to be a linear function of frequency and dynamic strain. Samples with a small concentration of just 0.57% of CNT show a sensitivity as high as 2.5% MPa-1 for static mechanical loading. A mathematical model based on Bruggeman's effective medium theory is developed to better understand the experimental results. Dynamic mechanical loading experiments reveal a sensitivity as high as 0.007% Hz(-1) at a constant small-amplitude vibration and up to 0.13%/mu-strain at 0-500 Hz vibration. Potential applications of such thin films include highly sensitive strain sensors, accelerometers, artificial neural networks, artificial skin and polymer electronics.

The dynamics of polymerized carbon nanotubes in semiconductor polymer electronics and electro-mechanical sensing

Polymerized carbon nanotubes (CNTs) are promising materials for polymer-based electronics and electro-mechanical sensors. The advantage of having a polymer nanolayer on CNTs widens the scope for functionalizing it in various ways for polymer electronic devices. However, in this paper, we show for the first time experimentally that, due to a resistive polymer layer having carbon nanoparticle inclusions and polymerized carbon nanotubes, an interesting dynamics can be exploited. We first show analytically that the relative change in the resistance of a single isolated semiconductive nanotube is directly proportional to the axial and torsional dynamic strains, when the strains are small, whereas, in polymerized CNTs, the viscoelasticity of the polymer and its effective electrical polarization give rise to nonlinear effects as a function of frequency and bias voltage. A simplified formula is derived to account for these effects and validated in the light of experimental results. CNT–polymer-based channels have been fabricated on a PZT substrate. Strain sensing performance of such a one-dimensional channel structure is reported. For a single frequency modulated sine pulse as input, which is common in elastic and acoustic wave-based diagnostics, imaging, microwave devices, energy harvesting, etc, the performance of the fabricated channel has been found to be promising.

Prediction of compressive strength of SCC and HPC with high volume fly ash using ANN

An artificial neural network (ANN) is presented to predict a 28-day compressive strength of a normal and high strength self compacting concrete (SCC) and high performance concrete (HPC) with high volume fly ash. The ANN is trained by the data available in literature on normal volume fly ash because data on SCC with high volume fly ash is not available in sufficient quantity. Further, while predicting the strength of HPC the same data meant for SCC has been used to train in order to economise on computational effort. The compressive strengths of SCC and HPC as well as slump flow of SCC estimated by the proposed neural network are validated by experimental results.

Spectral and thermal sensing for nitrogen and water status in rainfed and irrigated wheat environments

Variable-rate technologies and site-specific crop nutrient management require real-time spatial information about the potential for response to in-season crop management interventions. Thermal and spectral properties of canopies can provide relevant information for non-destructive measurement of crop water and nitrogen stresses. In previous studies, foliage temperature was successfully estimated from canopy-scale (mixed foliage and soil) temperatures and the multispectral Canopy Chlorophyll Content Index (CCCI) was effective in measuring canopy-scale N status in rainfed wheat (Triticum aestivum L.) systems in Horsham, Victoria, Australia. In the present study, results showed that under irrigated wheat systems in Maricopa, Arizona, USA, the theoretical derivation of foliage temperature unmixing produced relationships similar to those in Horsham. Derivation of the CCCI led to an r2 relationship with chlorophyll a of 0.53 after Zadoks stage 43. This was later than the relationship (r2 = 0.68) developed for Horsham after Zadoks stage 33 but early enough to be used for potential mid-season N fertilizer recommendations. Additionally, ground-based hyperspectral data estimated plant N (g kg)1) in Horsham with an r2 = 0.86 but was confounded by water supply and N interactions. By combining canopy thermal and spectral properties, varying water and N status can potentially be identified eventually permitting targeted N applications to those parts of a field where N can be used most efficiently by the crop.

Inter-lamellar shear resistance confers compressive stiffness in the intervertebral disc: An image-based modelling study on the bovine caudal disc

The intervertebral disc withstands large compressive loads (up to nine times bodyweight in humans) while providing flexibility to the spinal column. At a microstructural level, the outer sheath of the disc (the annulus fibrosus) comprises 12–20 annular layers of alternately crisscrossed collagen fibres embedded in a soft ground matrix. The centre of the disc (the nucleus pulposus) consists of a hydrated gel rich in proteoglycans. The disc is the largest avascular structure in the body and is of much interest biomechanically due to the high societal burden of disc degeneration and back pain. Although the disc has been well characterized at the whole joint scale, it is not clear how the disc tissue microstructure confers its overall mechanical properties. In particular, there have been conflicting reports regarding the level of attachment between adjacent lamellae in the annulus, and the importance of these interfaces to the overall integrity of the disc is unknown. We used a polarized light micrograph of the bovine tail disc in transverse cross-section to develop an image-based finite element model incorporating sliding and separation between layers of the annulus, and subjected the model to axial compressive loading. Validation experiments were also performed on four bovine caudal discs. Interlamellar shear resistance had a strong effect on disc compressive stiffness, with a 40% drop in stiffness when the interface shear resistance was changed from fully bonded to freely sliding. By contrast, interlamellar cohesion had no appreciable effect on overall disc mechanics. We conclude that shear resistance between lamellae confers disc mechanical resistance to compression, and degradation of the interlamellar interface structure may be a precursor to macroscopic disc degeneration.

Remote sensing of nitrogen and water stress in wheat

Nitrogen (N) is the largest agricultural input in many Australian cropping systems and applying the right amount of N in the right place at the right physiological stage is a significant challenge for wheat growers. Optimizing N uptake could reduce input costs and minimize potential off-site movement. Since N uptake is dependent on soil and plant water status, ideally, N should be applied only to areas within paddocks with sufficient plant available water. To quantify N and water stress, spectral and thermal crop stress detection methods were explored using hyperspectral, multispectral and thermal remote sensing data collected at a research field site in Victoria, Australia. Wheat was grown over two seasons with two levels of water inputs (rainfall/irrigation) and either four levels (in 2004; 0, 17, 39 and 163 kg/ha) or two levels (in 2005; 0 and 39 kg/ha N) of nitrogen. The Canopy Chlorophyll Content Index (CCCI) and modified Spectral Ratio planar index (mSRpi), two indices designed to measure canopy-level N, were calculated from canopy-level hyperspectral data in 2005. They accounted for 76% and 74% of the variability of crop N status, respectively, just prior to stem elongation (Zadoks 24). The Normalised Difference Red Edge (NDRE) index and CCCI, calculated from airborne multispectral imagery, accounted for 41% and 37% of variability in crop N status, respectively. Greater scatter in the airborne data was attributable to the difference in scale of the ground and aerial measurements (i.e., small area plant samples against whole-plot means from imagery). Nevertheless, the analysis demonstrated that canopy-level theory can be transferred to airborne data, which could ultimately be of more use to growers. Thermal imagery showed that mean plot temperatures of rainfed treatments were 2.7 °C warmer than irrigated treatments (P < 0.001) at full cover. For partially vegetated fields, the two-Dimensional Crop Water Stress Index (2D CWSI) was calculated using the Vegetation Index-Temperature (VIT) trapezoid method to reduce the contribution of soil background to image temperature. Results showed rainfed plots were consistently more stressed than irrigated plots. Future work is needed to improve the ability of the CCCI and VIT methods to detect N and water stress and apply both indices simultaneously at the paddock scale to test whether N can be targeted based on water status. Use of these technologies has significant potential for maximising the spatial and temporal efficiency of N applications for wheat growers. ‘Ground–breaking Stuff’- Proceedings of the 13th Australian Society of Agronomy Conference, 10-14 September 2006, Perth, Western Australia.

Affective sensing + wearable imaging: Vision impairment and implications for spatial enquiry

Recent interest in affect and the body have mobilized a contemporary review of aesthetics and phenomenology within architecture to unpack how environments affect spatial experience. Emerging spatial studies within the neuro-sciences, and their implications for architectural research as raised by architectural theorists Juhani Pallasmaa (2014) and Harry Mallgrave (2013) has been well supported by a raft of scientists and institutions including the prestigious Salk Institute. Although there has been some headway in spatial studies of the vision impaired (Cattaneo et al, 2011) to understand the role of their non-visual systems in assisting navigation and location, little is discussed in terms of their other abilities in sensing particular qualities of space which impinge upon emotion. This paper reviews a collection of studies exploring face vision and echo-location, amongst others, which provide insight into what might be termed affective perception of the vision impaired, and how further interplay between this research and the architectural field can contribute new knowledge regarding space and affect. By engaging with themes from the Aesthetics, Phenomenology and indeed Neuro-science fields, the paper provides background of current and potential cross disciplinary research, and highlights the role wearable technologies can play in enhancing knowledge of affective spatial experience.