Rapid nutrient determination of sugarcane milling by-products using near infrared spectroscopy

This thesis investigates the use of near infrared (NIR) spectroscopic methods for rapid measurement of nutrient elements in mill mud and mill ash. Adoption of NIR-based analyses for carbon, nitrogen, phosphorus, potassium and silicon will allow Australian sugarcane farmers to comply with recent legislative changes, and act within recommended precision farming frameworks. For these analyses, NIR spectroscopic methods surpass several facets of traditional wet chemistry techniques, dramatically reducing costs, required expertise and chemical exposure, while increasing throughput and access to data. Further, this technology can be applied in various modes, including laboratory, at-line and on-line installations, allowing targeted measurement.

HPLC method for preliminary analysis of constituents in rat blood after oral administration of the extract of Acanthopanax senticosus

An HPLC with SPE method has been developed for analysis of constituents in rat blood after oral administration of the extract of Acanthopanax senticosus (ASE). The plasma sample was prepared by SPE method equipped with Oasis HLB cartridge (3cc, 60 mg). The analysis was performed on a Dikma Diamonsil RP(18) column (4.6 mmx150 mm, 5 microm) with the gradient elution of solvent A (ACN) and solvent B (0.1% aqueous phosphoric acid, v/v) and the detection wavelength was set at 270 nm. The calibration curve was linear over the range of 0.156-15.625 microg/mL. The LOD was 60 ng/mL. The intraday precision was less than 5.80%, and the interday precision was less than 6.0%. The recovery was (87.30 +/- 1.73)%. As a result, 19 constituents were detected in rat plasma after oral administration of the ASE, including 11 original compounds in ASE and eight metabolites, and three of the metabolites originated from syringin in ASE. Six constituents were identified by comparing with the corresponding reference compounds.

Shoes that restrict metatarsophalangeal dorsiflexion cause proximal joint compensations

To describe barefoot, shod and in-shoe kinematics during stance phase of walking gait in a normal arched adult population. An equal sample of males and females (n = 24) was recruited. In order to quantify the effect of footwear independent of technical design features, an ASICS shoe (Onitsuka Tiger-Mexico 66, Japan) was used in this study. Markers were applied to three conditions; barefoot, shod, and in-shoe. The calibration markers were used to define static pose. The order of testing was randomised. Participants completed five trials in each condition. Kinematic data were captured using a 12 camera VICON MX40 motion capture system at 100 Hz and processed in Visual3D. A previously developed model was used to describe joint angles [1]. A univariate two-way ANOVA was used to identify any differences between the pairs of conditions. Post-hoc Sheffé tests were used to further interrogate the data for differences. At peak hallux dorsiflexion (Figure 1), during propulsion, the metatarsophalangeal joint (MPTJ) was significantly more dorsiflexed in the barefoot condition compared to the shod condition (p = 0.004). At the same gait event, the tibiocalcaneal joint (TCJ) was significantly more plantarflexed than both the shod and in-shoe conditions (p < 0.001), and the tarsometatarsal joint (TMTJ) was significantly less dorsiflexed in the barefoot condition compared to the shod and in-shoe conditions (p < 0.001). The findings of the current study demonstrate that footwear has significant effects on sagittal plane MPTJ joint dorsiflexion at peak hallux dorsiflexion, which results in compensations at proximal foot joints.

Made by motion, Series one

“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 generating 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 this first series the visual investigation focused on manipulating the movement date at the instance of capture, capture been the recording of three-dimensional movement as ‘seen’ by the hardware and ‘understood’ through the calibration of software. By repositioning the capture hardware on the body we can effectively change how the same sequence of movements is ‘seen’ by the motion capture system thus generating a different visual result from effetely identical movement. The outcomes from the experiments clearly demonstrates the effectiveness of using motion capture hardware as a creative tool to manipulate the perception of the capture subject, in this case been a sequence of dance movements. The creative work exhibited is a cross-section of the experiments conducted in practice with the first animated work (Movement A - Control) using the motion capture hardware in its default ‘normal’ configuration. Following this is the lower body moved to the upper body (Lb-Ub), right arm moved onto the left arm (Ra-La), right leg moved onto the left leg (Rl-Ll) and finally the left leg moved onto a object that is then held in the left hand (Ll-Pf (Lh)).

A computer image analysis system for microvessel density measurement in solid tumours

Microvessel density (MVD) is a widely used surrogate measure of angiogenesis in pathological specimens and tumour models. Measurement of MVD can be achieved by several methods. Automation of counting methods aims to increase the speed, reliability and reproducibility of these techniques. The image analysis system described here enables MVD measurement to be carried out with minimal expense in any reasonably equipped pathology department or laboratory. It is demonstrated that the system translates easily between tumour types which are suitably stained with minimal calibration. The aim of this paper is to offer this technique to a wider field of researchers in angiogenesis.

The essential parameters of a resource-based carrying capacity assessment model : an Australian case study

Carrying capacity assessments model a population’s potential self-sufficiency. A crucial first step in the development of such modelling is to examine the basic resource-based parameters defining the population’s production and consumption habits. These parameters include basic human needs such as food, water, shelter and energy together with climatic, environmental and behavioural characteristics. Each of these parameters imparts land-usage requirements in different ways and varied degrees so their incorporation into carrying capacity modelling also differs. Given that the availability and values of production parameters may differ between locations, no two carrying capacity models are likely to be exactly alike. However, the essential parameters themselves can remain consistent so one example, the Carrying Capacity Dashboard, is offered as a case study to highlight one way in which these parameters are utilised. While examples exist of findings made from carrying capacity assessment modelling, to date, guidelines for replication of such studies in other regions and scales have largely been overlooked. This paper addresses such shortcomings by describing a process for the inclusion and calibration of the most important resource-based parameters in a way that could be repeated elsewhere.

A Near-Infrared Reflectance Spectroscopy Method for Direct Analysis of Several Chemical Components and Properties of Fruit, for Example, Chinese Hawthorn

Near-infrared spectroscopy (NIRS) calibrations were developed for the discrimination of Chinese hawthorn (Crataegus pinnatifida Bge. var. major) fruit from three geographical regions as well as for the estimation of the total sugar, total acid, total phenolic content, and total antioxidant activity. Principal component analysis (PCA) was used for the discrimination of the fruit on the basis of their geographical origin. Three pattern recognition methods, linear discriminant analysis, partial least-squares-discriminant analysis, and back-propagation artificial neural networks, were applied to classify and compare these samples. Furthermore, three multivariate calibration models based on the first derivative NIR spectroscopy, partial least-squares regression, back-propagation artificial neural networks, and least-squares-support vector machines, were constructed for quantitative analysis of the four analytes, total sugar, total acid, total phenolic content, and total antioxidant activity, and validated by prediction data sets.

Fine tuning of elasticity via crosslinking collagen-based materials to mediate mechanotransduction and stability using corona treatment

The common goal of tissue engineering is to develop substitutes that can closely mimic the structure of extracellular matrix (ECM). However, similarly important is the intensive material properties which have often been overlooked, in particular, for soft tissues that are not to bear load assumingly. The mechanostructural properties determine not only the structural stability of biomaterials but also their physiological functionality by directing cellular activity and regulating cell fate decision. The aim here is to emphasize that cells could sense intensive material properties like elasticity and reside, proliferate, migrate and differentiate accordinglyno matter if the construct is from a natural source like cartilage, skin etc. or of synthetic one. Meanwhile, the very objective of this work is to provide a tunable scheme for manipulating the elasticity of collagen-based constructs to be used to demonstrate how to engineer cell behavior and regulate mechanotransduction. Articular cartilage was chosen as it represents one of the most complex hierarchical arrangements of collagen meshwork in both connective tissues and ECM-like biomaterials. Corona discharge treatment was used to produce constructs with varying density of crosslinked collagen and stiffness accordingly. The results demonstrated that elastic modulus increased up to 33% for samples treated up to one minute as crosslink density was found to increase with exposure time. According to the thermal analysis, longer exposure to corona increased crosslink density as the denaturation enthalpy increased. However the spectroscopy results suggested that despite the stabilization of the collagen structure the integrity of the triple helical structure remained intact. The in vitro superficial culture of heterologous chondrocytes also determined that the corona treatment can modulate migration with increased focal adhesion of cells due to enhanced stiffness, without cytotoxicity effects, and providing the basis for reinforcing three-dimensional collagen-based biomaterials in order to direct cell function and mediate mechanotransduction.

Dealing with shadows : capturing intrinsic scene appearance for image-based outdoor localisation

In outdoor environments shadows are common. These typically strong visual features cause considerable change in the appearance of a place, and therefore confound vision-based localisation approaches. In this paper we describe how to convert a colour image of the scene to a greyscale invariant image where pixel values are a function of underlying material property not lighting. We summarise the theory of shadow invariant images and discuss the modelling and calibration issues which are important for non-ideal off-the-shelf colour cameras. We evaluate the technique with a commonly used robotic camera and an autonomous car operating in an outdoor environment, and show that it can outperform the use of ordinary greyscale images for the task of visual localisation.

Sterilizing tissue-materials using pulsed power plasma

This paper investigates the potential of pulsed power to sterilize hard and soft tissues and its impact on their physico-mechanical properties. It hypothesizes that pulsed plasma can sterilize both vascular and avascular tissues and the transitive layers in between without deleterious effects on their functional characteristics. Cartilage/bone laminate was chosen as a model to demonstrate the concept, treated at low temperature, at atmospheric pressure, in short durations and in buffered environment using a purposed-built pulsed power unit. Input voltage and time of exposure were assigned as controlling parameters in a full factorial design of experiment to determine physical and mechanical alteration pre- and post-treatment. The results demonstrated that, discharges of 11 kV sterilized samples in 45 s, reducing intrinsic elastic modules from 1.4 ± 0.9 to 0.9 ± 0.6 MPa. There was a decrease of 14.1 % in stiffness and 27.8 % in elastic-strain energy for the top quartile. Mechanical impairment was directly proportional to input voltage (P value < 0.05). Bacterial inactivation was proportional to treatment time for input voltages above 32 V (P < 0.001; R Sq = 0.98). Thermal analysis revealed that helix-coil transition decelerated with exposure time and collagen fibrils were destabilized as denaturation enthalpy reduced by 200 μV. We concluded by presenting a safe operating threshold for pulsed power plasma as a feasible protocol for effective sterilization of connective tissues with varying level of loss in mechanical robustness which we argue to be acceptable in certain medical and tissue engineering application.

Total heat transfer measurements on a flight investigation of reentry environment model

Stagnation-point total heat transfer was measured on a 1:27.7 model of the Flight Investigation of Reentry Environment II flight vehicle. Experiments were performed in the X1 expansion tube at an equivalent flight velocity and static enthalpy of 11 km/s and 12.7 MJ/kg, respectively. Conditions were chosen to replicate the flight condition at a total flight time of 1639.5 s, where radiation contributed an estimated 17-36% of the total heat transfer. This contribution is theorized to reduce to <2% in the scaled experiments, and the heating environment on the test model was expected to be dominated by convection. A correlation between reported flight heating rates and expected experimental heating, referred to as the reduced flight value, was developed to predict the level of heating expected on the test model. At the given flow conditions, the reduced flight value was calculated to be 150 MW/m2. Average stagnation-point total heat transfer was measured to be 140 ± 7% W/m2, showing good agreement with the predicted value. Experimentally measured heat transfer was found to have good agreement of between 5 and 15% with a number of convective heating correlations, confirming that convection dominates the tunnel heating environment, and that useful experimental measurements could be made in weakly coupled radiating flow

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.

Sensor Data Integrity : Multi-Sensor Perception for Unmanned Ground Vehicles

This document describes large, accurately calibrated and time-synchronised datasets, gathered in controlled environmental conditions, using an unmanned ground vehicle equipped with a wide variety of sensors. These sensors include: multiple laser scanners, a millimetre wave radar scanner, a colour camera and an infra-red camera. Full details of the sensors are given, as well as the calibration parameters needed to locate them with respect to each other and to the platform. This report also specifies the format and content of the data, and the conditions in which the data have been gathered. The data collection was made in two different situations of the vehicle: static and dynamic. The static tests consisted of sensing a fixed ’reference’ terrain, containing simple known objects, from a motionless vehicle. For the dynamic tests, data were acquired from a moving vehicle in various environments, mainly rural, including an open area, a semi-urban zone and a natural area with different types of vegetation. For both categories, data have been gathered in controlled environmental conditions, which included the presence of dust, smoke and rain. Most of the environments involved were static, except for a few specific datasets which involve the presence of a walking pedestrian. Finally, this document presents illustrations of the effects of adverse environmental conditions on sensor data, as a first step towards reliability and integrity in autonomous perceptual systems.

Handheld 3D thermography using range sensing and computer vision

This thesis developed a method for real-time and handheld 3D temperature mapping using a combination of off-the-shelf devices and efficient computer algorithms. It contributes a new sensing and data processing framework to the science of 3D thermography, unlocking its potential for application areas such as building energy auditing and industrial monitoring. New techniques for the precise calibration of multi-sensor configurations were developed, along with several algorithms that ensure both accurate and comprehensive surface temperature estimates can be made for rich 3D models as they are generated by a non-expert user.

Bayesian imputation of non-chosen attribute values in revealed preference surveys

Obtaining attribute values of non-chosen alternatives in a revealed preference context is challenging because non-chosen alternative attributes are unobserved by choosers, chooser perceptions of attribute values may not reflect reality, existing methods for imputing these values suffer from shortcomings, and obtaining non-chosen attribute values is resource intensive. This paper presents a unique Bayesian (multiple) Imputation Multinomial Logit model that imputes unobserved travel times and distances of non-chosen travel modes based on random draws from the conditional posterior distribution of missing values. The calibrated Bayesian (multiple) Imputation Multinomial Logit model imputes non-chosen time and distance values that convincingly replicate observed choice behavior. Although network skims were used for calibration, more realistic data such as supplemental geographically referenced surveys or stated preference data may be preferred. The model is ideally suited for imputing variation in intrazonal non-chosen mode attributes and for assessing the marginal impacts of travel policies, programs, or prices within traffic analysis zones.