A novel method using intranasal delivery of EdU demonstrates that accessory olfactory ensheathing cells respond to injury by proliferation

Olfactory ensheathing cells (OECs) play an important role in the continuous regeneration of the primary olfactory nervous system throughout life and for regeneration of olfactory neurons after injury. While it is known that several individual OEC subpopulations with distinct properties exist in different anatomical locations, it remains unclear how these different subpopulations respond to a major injury. We have examined the proliferation of OECs from one distinct location, the peripheral accessory olfactory nervous system, following large-scale injury (bulbectomy) in mice. We used crosses of two transgenic reporter mouse lines, S100ß-DsRed and OMP-ZsGreen, to visualise OECs, and main/accessory olfactory neurons, respectively. We surgically removed one olfactory bulb including the accessory olfactory bulb to induce degeneration, and found that accessory OECs in the nerve bundles that terminate in the accessory olfactory bulb responded by increased proliferation with a peak occurring 2 days after the injury. To label proliferating cells we used the thymidine analogue ethynyl deoxyuridine (EdU) using intranasal delivery instead of intraperitoneal injection. We compared and quantified the number of proliferating cells at different regions at one and four days after EdU labelling by the two different methods and found that intranasal delivery method was as effective as intrapeitoneal injection. We demonstrated that accessory OECs actively respond to widespread degeneration of accessory olfactory axons by proliferating. These results have important implications for selecting the source of OECs for neural regeneration therapies and show that intranasal delivery of EdU is an efficient and reliable method for assessing proliferation of olfactory glia.

A feasibility study of multislice x-ray CT imaging of gel dosimeters using the “zero scan” method

This study extends the ‘zero scan’ method for CT imaging of polymer gel dosimeters to include multi-slice acquisitions. Multi slice CT images consisting of 24 slices of 1.2 mm thickness were acquired of an irradiated polymer gel dosimeter, and processed with the zero scan technique. The results demonstrate that zero scan based gel readout can be successfully applied to generate a three dimensional image of the irradiated gel field. Compared to the raw CT images the processed figures and cross gel profiles demonstrated reduced noise and clear visibility of the penumbral region. Moreover these improved results further highlight the suitability of this method in volumetric reconstruction with reduced CT data acquisition per slice. This work shows that 3D volumes of irradiated polymer gel dosimeters can be acquired and processed with x-ray CT.

Perception Quality Evaluation with Visual and Infrared Cameras in Challenging Environmental Conditions

This work aims to contribute to the reliability and integrity of perceptual systems of unmanned ground vehicles (UGV). A method is proposed to evaluate the quality of sensor data prior to its use in a perception system by utilising a quality metric applied to heterogeneous sensor data such as visual and infrared camera images. The concept is illustrated specifically with sensor data that is evaluated prior to the use of the data in a standard SIFT feature extraction and matching technique. The method is then evaluated using various experimental data sets that were collected from a UGV in challenging environmental conditions, represented by the presence of airborne dust and smoke. In the first series of experiments, a motionless vehicle is observing a ’reference’ scene, then the method is extended to the case of a moving vehicle by compensating for its motion. This paper shows that it is possible to anticipate degradation of a perception algorithm by evaluating the input data prior to any actual execution of the algorithm.

Tuning the surface structure of nitrogen-doped TiO2Nanofibres : an effective method to rnhance photocatalytic activities of visible-light-driven green synthesis and degradation

Nitrogen-doped TiO2 nanofibres of anatase and TiO2(B) phases were synthesised by a reaction between titanate nanofibres of a layered structure and gaseous NH3 at 400–700 °C, following a different mechanism than that for the direct nitrogen doping from TiO2. The surface of the N-doped TiO2 nanofibres can be tuned by facial calcination in air to remove the surface-bonded N species, whereas the core remains N doped. N-Doped TiO2 nanofibres, only after calcination in air, became effective photocatalysts for the decomposition of sulforhodamine B under visible-light irradiation. The surface-oxidised surface layer was proven to be very effective for organic molecule adsorption, and the activation of oxygen molecules, whereas the remaining N-doped interior of the fibres strongly absorbed visible light, resulting in the generation of electrons and holes. The N-doped nanofibres were also used as supports of gold nanoparticle (Au NP) photocatalysts for visible-light-driven hydroamination of phenylacetylene with aniline. Phenylacetylene was activated on the N-doped surface of the nanofibres and aniline on the Au NPs. The Au NPs adsorbed on N-doped TiO2(B) nanofibres exhibited much better conversion (80 % of phenylacetylene) than when adsorbed on undoped fibres (46 %) at 40 °C and 95 % of the product is the desired imine. The surface N species can prevent the adsorption of O2 that is unfavourable for the hydroamination reaction, and thus, improve the photocatalytic activity. Removal of the surface N species resulted in a sharp decrease of the photocatalytic activity. These photocatalysts are feasible for practical applications, because they can be easily dispersed into solution and separated from a liquid by filtration, sedimentation or centrifugation due to their fibril morphology.

High-growth firms : characteristics, job contribution and method observations

Largely as a result of mass unemployment problems in many European countries, the dynamics of job creation has in recent years attracted increased interest on the part of academics as well as policy-makers. In connection to this, a large number of studies carried out in various countries have concluded that SMEs play a very large and/or growing role as job creators (Birch, 1979; Baldwin and Picot, 1995; Davidsson, 1995a; Davidsson, Lindmark and Olofsson, 1993; 1994; 1995; 1997a; 1997b; Fumagelli and Mussati, 1993; Kirchhoff and Phillips, 1988; Spilling, 1995; for further reference to studies carried out in a large number of countries see also Aiginger and Tichy, 1991; ENSR, 1994; Loveman and Sengenberger, 1991; OECD, 1987; Storey and Johnson, 1987). While most researchers agree on the importance of SMEs, there is some controversy as regards whether this is mainly a result of many small start-ups and incremental expansions, or if a small minority of high growth SMEs contribute the lion’s share of new employment. This is known as the ‘mice vs. gazelles’ or ‘flyers vs. trundlers’ debate. Storey strongly advocates the position that the small group of high growth SMEs are the ‘real’ job creators (Storey, 1994; Storey & Johnson, 1987), whereas, e.g., the Davidsson et al research in Sweden (cf. above) gives more support for the ‘mice’ hypothesis.

A finite volume method with linearisation in time for the solution of advection-reaction-diffusion systems

The numerical solution in one space dimension of advection--reaction--diffusion systems with nonlinear source terms may invoke a high computational cost when the presently available methods are used. Numerous examples of finite volume schemes with high order spatial discretisations together with various techniques for the approximation of the advection term can be found in the literature. Almost all such techniques result in a nonlinear system of equations as a consequence of the finite volume discretisation especially when there are nonlinear source terms in the associated partial differential equation models. This work introduces a new technique that avoids having such nonlinear systems of equations generated by the spatial discretisation process when nonlinear source terms in the model equations can be expanded in positive powers of the dependent function of interest. The basis of this method is a new linearisation technique for the temporal integration of the nonlinear source terms as a supplementation of a more typical finite volume method. The resulting linear system of equations is shown to be both accurate and significantly faster than methods that necessitate the use of solvers for nonlinear system of equations.

A deconvolution method for deriving the transit time spectrum for ultrasound propagation through cancellous bone replica models

The acceptance of broadband ultrasound attenuation for the assessment of osteoporosis suffers from a limited understanding of ultrasound wave propagation through cancellous bone. It has recently been proposed that the ultrasound wave propagation can be described by a concept of parallel sonic rays. This concept approximates the detected transmission signal to be the superposition of all sonic rays that travel directly from transmitting to receiving transducer. The transit time of each ray is defined by the proportion of bone and marrow propagated. An ultrasound transit time spectrum describes the proportion of sonic rays having a particular transit time, effectively describing lateral inhomogeneity of transit times over the surface of the receiving ultrasound transducer. The aim of this study was to provide a proof of concept that a transit time spectrum may be derived from digital deconvolution of input and output ultrasound signals. We have applied the active-set method deconvolution algorithm to determine the ultrasound transit time spectra in the three orthogonal directions of four cancellous bone replica samples and have compared experimental data with the prediction from the computer simulation. The agreement between experimental and predicted ultrasound transit time spectrum analyses derived from Bland–Altman analysis ranged from 92% to 99%, thereby supporting the concept of parallel sonic rays for ultrasound propagation in cancellous bone. In addition to further validation of the parallel sonic ray concept, this technique offers the opportunity to consider quantitative characterisation of the material and structural properties of cancellous bone, not previously available utilising ultrasound.

Australian animated feature films

Building on and bringing up to date the material presented in the first installment of Directory of World Cinema : Australia and New Zealand, this volume continues the exploration of the cinema produced in Australia and New Zealand since the beginning of the twentieth century. Among the additions to this volume are in-depth treatments of the locations that feature prominently in the countries' cinema. Essays by leading critics and film scholars consider the significance in films of the outback and the beach, which is evoked as a liminal space in Long Weekend and a symbol of death in Heaven's Burning, among other films. Other contributions turn the spotlight on previously unexplored genres and key filmmakers, including Jane Campion, Rolf de Heer, Charles Chauvel, and Gillian Armstrong.

Mining specific features for acquiring user information needs

Term-based approaches can extract many features in text documents, but most include noise. Many popular text-mining strategies have been adapted to reduce noisy information from extracted features; however, text-mining techniques suffer from low frequency. The key issue is how to discover relevance features in text documents to fulfil user information needs. To address this issue, we propose a new method to extract specific features from user relevance feedback. The proposed approach includes two stages. The first stage extracts topics (or patterns) from text documents to focus on interesting topics. In the second stage, topics are deployed to lower level terms to address the low-frequency problem and find specific terms. The specific terms are determined based on their appearances in relevance feedback and their distribution in topics or high-level patterns. We test our proposed method with extensive experiments in the Reuters Corpus Volume 1 dataset and TREC topics. Results show that our proposed approach significantly outperforms the state-of-the-art models.

An autonomous surface vehicle for water quality monitoring

This paper describes a novel Autonomous Surface Vehicle capable of navigating throughout complex inland water storages and measuring a range of water quality properties and greenhouse gas emissions. The 16 ft long solar powered catamaran can collect this information throughout the water column whilst the vehicle is moving. A unique feature of this ASV is its integration into a storage scale floating sensor network to allow remote mission uploads, data download and adaptive sampling strategies. This paper provides an overview of the vehicle design and operation including control, laser-based obstacle avoidance, and vision-based inspection capabilities. Experimental results are shown illustrating its ability to continuously collect key water quality parameters and compliment intensive manual monitoring campaigns.

A finite volume method for solving the two-sided time-space fractional advection-dispersion equation

We present a finite volume method to solve the time-space two-sided fractional advection-dispersion equation on a one-dimensional domain. The spatial discretisation employs fractionally-shifted Grünwald formulas to discretise the Riemann-Liouville fractional derivatives at control volume faces in terms of function values at the nodes. We demonstrate how the finite volume formulation provides a natural, convenient and accurate means of discretising this equation in conservative form, compared to using a conventional finite difference approach. Results of numerical experiments are presented to demonstrate the effectiveness of the approach.

A rule-based hybrid method for anomaly detection in online-social-network graphs

Detecting anomalies in the online social network is a significant task as it assists in revealing the useful and interesting information about the user behavior on the network. This paper proposes a rule-based hybrid method using graph theory, Fuzzy clustering and Fuzzy rules for modeling user relationships inherent in online-social-network and for identifying anomalies. Fuzzy C-Means clustering is used to cluster the data and Fuzzy inference engine is used to generate rules based on the cluster behavior. The proposed method is able to achieve improved accuracy for identifying anomalies in comparison to existing methods.

A novel process of group-oriented question reduction for rule-based recommendation websites

Several websites utilise a rule-base recommendation system, which generates choices based on a series of questionnaires, for recommending products to users. This approach has a high risk of customer attrition and the bottleneck is the questionnaire set. If the questioning process is too long, complex or tedious; users are most likely to quit the questionnaire before a product is recommended to them. If the questioning process is short; the user intensions cannot be gathered. The commonly used feature selection methods do not provide a satisfactory solution. We propose a novel process combining clustering, decisions tree and association rule mining for a group-oriented question reduction process. The question set is reduced according to common properties that are shared by a specific group of users. When applied on a real-world website, the proposed combined method outperforms the methods where the reduction of question is done only by using association rule mining or only by observing distribution within the group.

Outdoor flight testing of a pole inspection UAV incorporating high-speed vision

We present a pole inspection system for outdoor environments comprising a high-speed camera on a vertical take-off and landing (VTOL) aerial platform. The pole inspection task requires a vehicle to fly close to a structure while maintaining a fixed stand-off distance from it. Typical GPS errors make GPS-based navigation unsuitable for this task however. When flying outdoors a vehicle is also affected by aerodynamics disturbances such as wind gusts, so the onboard controller must be robust to these disturbances in order to maintain the stand-off distance. Two problems must therefor be addressed: fast and accurate state estimation without GPS, and the design of a robust controller. We resolve these problems by a) performing visual + inertial relative state estimation and b) using a robust line tracker and a nested controller design. Our state estimation exploits high-speed camera images (100Hz) and 70Hz IMU data fused in an Extended Kalman Filter (EKF). We demonstrate results from outdoor experiments for pole-relative hovering, and pole circumnavigation where the operator provides only yaw commands. Lastly, we show results for image-based 3D reconstruction and texture mapping of a pole to demonstrate the usefulness for inspection tasks.

Novel sequential methods in dose-finding designs : extensions of the continual reassessment method

Dose-finding trials are a form of clinical data collection process in which the primary objective is to estimate an optimum dose of an investigational new drug when given to a patient. This thesis develops and explores three novel dose-finding design methodologies. All design methodologies presented in this thesis are pragmatic. They use statistical models, incorporate clinicians' prior knowledge efficiently, and prematurely stop a trial for safety or futility reasons. Designing actual dose-finding trials using these methodologies will minimize practical difficulties, improve efficiency of dose estimation, be flexible to stop early and reduce possible patient discomfort or harm.